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  Subjects -> COMPUTER SCIENCE (Total: 2153 journals)
    - ANIMATION AND SIMULATION (31 journals)
    - ARTIFICIAL INTELLIGENCE (106 journals)
    - AUTOMATION AND ROBOTICS (106 journals)
    - CLOUD COMPUTING AND NETWORKS (67 journals)
    - COMPUTER ARCHITECTURE (10 journals)
    - COMPUTER ENGINEERING (11 journals)
    - COMPUTER GAMES (22 journals)
    - COMPUTER PROGRAMMING (26 journals)
    - COMPUTER SCIENCE (1258 journals)
    - COMPUTER SECURITY (50 journals)
    - DATA BASE MANAGEMENT (13 journals)
    - DATA MINING (38 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (31 journals)
    - ELECTRONIC DATA PROCESSING (22 journals)
    - IMAGE AND VIDEO PROCESSING (40 journals)
    - INFORMATION SYSTEMS (107 journals)
    - INTERNET (97 journals)
    - SOCIAL WEB (53 journals)
    - SOFTWARE (34 journals)
    - THEORY OF COMPUTING (9 journals)

COMPUTER SCIENCE (1258 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 25)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 31)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 9)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 17)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 9)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 16)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 8)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 6)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 20)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 35)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 10)
Advanced Engineering Materials     Hybrid Journal   (Followers: 29)
Advanced Science Letters     Full-text available via subscription   (Followers: 11)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 9)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 6)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 20)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computer Science : an International Journal     Open Access   (Followers: 16)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 58)
Advances in Engineering Software     Hybrid Journal   (Followers: 29)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 17)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 21)
Advances in Materials Science     Open Access   (Followers: 15)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 52)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 6)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 5)
AI EDAM     Hybrid Journal   (Followers: 2)
Air, Soil & Water Research     Open Access   (Followers: 14)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 7)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 5)
American Journal of Information Systems     Open Access   (Followers: 6)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 4)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annals of West University of Timisoara - Mathematics and Computer Science     Open Access   (Followers: 1)
Annual Reviews in Control     Hybrid Journal   (Followers: 8)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Applied Clinical Informatics     Hybrid Journal   (Followers: 3)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 14)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 34)
Applied Medical Informatics     Open Access   (Followers: 12)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 17)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 7)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 6)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 156)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 8)
Artifact     Open Access   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 6)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 13)
Automation in Construction     Hybrid Journal   (Followers: 8)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Balkan Journal of Electrical and Computer Engineering     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 4)
Biodiversity Information Science and Standards     Open Access   (Followers: 1)
Bioinformatics     Hybrid Journal   (Followers: 345)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 36)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 49)
British Journal of Educational Technology     Hybrid Journal   (Followers: 177)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Bulletin of Social Informatics Theory and Application     Open Access  
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 4)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals : X     Open Access  
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 8)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Hybrid Journal   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Clinical eHealth     Open Access  
Cluster Computing     Hybrid Journal   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 3)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 14)
Communication Theory     Hybrid Journal   (Followers: 25)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 3)
Communications in Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 4)
Communications of the ACM     Full-text available via subscription   (Followers: 52)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 4)
Computational and Mathematical Biophysics     Open Access   (Followers: 1)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 1)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 13)
Computational Chemistry     Open Access   (Followers: 3)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 10)
Computational Economics     Hybrid Journal   (Followers: 10)
Computational Geosciences     Hybrid Journal   (Followers: 18)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 10)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 8)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access   (Followers: 1)
Computational Statistics     Hybrid Journal   (Followers: 15)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 36)
Computer     Full-text available via subscription   (Followers: 106)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)

        1 2 3 4 5 6 7 | Last

Similar Journals
Journal Cover
Computer Communications
Journal Prestige (SJR): 0.459
Citation Impact (citeScore): 3
Number of Followers: 16  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0140-3664 - ISSN (Online) 0140-3664
Published by Elsevier Homepage  [3185 journals]
  • h -Mitigators:+Improving+your+stochastic+network+calculus+output+bounds&rft.title=Computer+Communications&rft.issn=0140-3664&rft.date=&rft.volume="> h -Mitigators: Improving your stochastic network calculus output bounds
    • Abstract: Publication date: 15 August 2019Source: Computer Communications, Volume 144Author(s): Paul Nikolaus, Jens Schmitt, Malte Schütze Giving tight estimates for output bounds is key to an accurate network analysis using the stochastic network calculus (SNC) framework. In order to upper bound the delay for a flow of interest in the network, one typically has to calculate output bounds of cross-traffic flows several times. Thus, an improvement in the output bound calculation pays off considerably. In this paper, we propose a new output bound calculation in the SNC framework by making use of Jensen’s inequality. In consists of inserting a convex function h into the bound, the so-called h-mitigator. We prove the bound’s validity and also show that, by choosing h as the power function, that it is always at least as accurate as the state-of-the-art method. Numerical evaluations demonstrate that even in small heterogeneous two-server topologies, our approach can improve a delay bound’s violation probability by a factor of over 135. For a set of randomly generated parameters, the bound is still decreased by a factor of 1.23 on average. Furthermore, our approach can be easily integrated in existing end-to-end analyses. Last but not least, we investigated another variant for h, the exponential function and showed numerically that this approach is mostly disadvantageous.
       
  • DAMS: D2D-assisted multimedia streaming service with minimized BS transmit
           power in cellular networks
    • Abstract: Publication date: 15 August 2019Source: Computer Communications, Volume 144Author(s): Pradip Kumar Barik, Chetna Singhal, Raja Datta This paper presents a scheme, named D2D-assisted Multimedia Streaming (DAMS), for selecting relay nodes to assist low-battery active users in a cellular network. The scheme also minimizes the transmission power of base stations (BSs) by transmitting data through D2D relay nodes (DRNs). The proposed scheme uses a maximum-weight bipartite matching and transmission power allocation algorithm to obtain optimal power allocation at the BS. We show that the energy required at the BS for transmitting D2D control signals is negligible in comparison to the transmission power that is saved. Simulation results verify the improved performance of the proposed scheme.
       
  • A trust management framework for clouds
    • Abstract: Publication date: 15 August 2019Source: Computer Communications, Volume 144Author(s): Yefeng Ruan, Arjan Durresi In today’s cloud computing platforms, more and more users are now working or collaborating in the multi-cloud environment, in which collaborators, clouds, computing nodes may belong to different institutions or organizations. Those different organizations might have their policies. Security is still a big concern in cloud computing. To help cloud vendors and customers to detect and prevent from being affected by potential attacks, we propose a trust management framework. We consider link/flow’s level trust, node’s level trust, and task/mission’s level trust.We introduced a new security metric trustability (trust–reliability) and a new algorithm to calculate it. Trustability measures how much a system can be trusted under a specific attack vector. Trustability can be used to explore the design space of resource configuration in order be able to choose the right trade-off between trustability and cost of redundancy. We show that our trust management framework can guide the administrators and customers to make decisions. For example, based on the real-time trust information, cloud administrators can migrate tasks from suspect nodes to trustworthy nodes, dynamically allocate a resource, and manage the trade-off between the degree of redundancy and the cost of the resource.
       
  • Clustered robust routing for traffic engineering in software-defined
           networks
    • Abstract: Publication date: 15 August 2019Source: Computer Communications, Volume 144Author(s): Davide Sanvito, Ilario Filippini, Antonio Capone, Stefano Paris, Jérémie Leguay One of the key advantages of Software-Defined Networks (SDN) is the opportunity to integrate Traffic Engineering modules able to optimize network configuration according to traffic. Ideally, the network should be dynamically reconfigured as traffic evolves, so as to achieve remarkable gains in the efficient use of resources with respect to traditional static approaches. Unfortunately, reconfigurations cannot be too frequent due to a number of reasons related to route stability, forwarding rules instantiation, individual flows dynamics, traffic monitoring overhead, etc.In this paper, we focus on the fundamental problem of deciding whether, when and how to reconfigure the network during traffic evolution. We propose a new approach to cluster relevant points in the multi-dimensional traffic space taking into account similarities in multiple domains and not only in traffic values. Moreover, to provide more flexibility to the decisions on when to apply a reconfiguration, we allow some overlap between clusters that can guarantee a good-quality routing even in case of smooth transitions.We compare our algorithm with state-of-the-art approaches in realistic network scenarios. Results show that our method significantly reduces the number of reconfigurations with a negligible deviation of the network performance with respect to the continuous update of the network configuration.Moreover, we present an experimental platform where our solution is implemented in a production-ready SDN controller.
       
  • Achieving liability in anonymous communication: Auditing and tracing
    • Abstract: Publication date: Available online 11 June 2019Source: Computer CommunicationsAuthor(s): Haibin Zheng, Qianhong Wu, Zhenyu Guan, Bo Qin, Shuangyu He, Jianwei Liu The emergence of anonymity abusing in anonymous communication has received considerable attention. Achieving the liability of auditing and tracing illegal users becomes to be a critical requirement. Although some anonymity abusing control strategies have been proposed, they mostly possess no prior audit judgment function. In this paper, we propose a linkable group signature mechanism to simultaneously achieve the functions of anonymity, auditing and tracing for communication sender. Specifically, we propose a general construction of linkable group signature using the basic cryptography modules of blind signature, public key encryption, trapdoor indicative commitment and signature of knowledge, and further extend it to a multi-authority environment based on distributed key generation protocol. Following the frameworks, we present concrete linkable group signature instances. Security and performance analyses confirm that our schemes are practical. Furthermore, we first formally define a new concept called trapdoor indicative commitment, which is applicable to judge whether given committed values are equal without opening the commitments.
       
  • Radio and computing resource allocation with energy harvesting devices in
           mobile edge computing environment
    • Abstract: Publication date: Available online 10 June 2019Source: Computer CommunicationsAuthor(s): Chunlin Li, Weining Chen, Jianhang Tang, Youlong Luo Mobile edge computing (MEC) has been recognized as a promising technique for the Internet of Things (IoT) era which allow the booming mobile devices offload their highly demanding tasks to the MEC server thus release these resource-limited devices from poor computational efficiency. With the development of wireless energy transfer (WET), the combination of wireless devices and energy harvesting technique has attracted much more interests. Energy harvesting enabled devices can be powered by the wireless energy signal to prolong their lifetime. For an MEC system with energy harvesting devices, how to make appropriate computation and communication resources allocation policy is still challenging. In this paper, we proposed a time average computation rate maximization (TACRM) algorithm that allows the joint allocation of radio and computation resources. In each time block, optimal bandwidths, transmit powers, time allocations for local computing and task offloading, and the local CPU frequencies are dynamically decided by the proposed algorithm. Theoretical performance analysis and extensive simulation verified that the proposed algorithm can effectively improve the system performance and outperforms the benchmark schemes.
       
  • A framework for the evaluation of routing protocols in opportunistic
           networks
    • Abstract: Publication date: Available online 8 June 2019Source: Computer CommunicationsAuthor(s): Dimitrios-Georgios Akestoridis, Evangelos Papapetrou The evaluation of routing protocols for opportunistic networks can be seen as a multidimensional problem because it involves several performance aspects. To capture these aspects various evaluation metrics are used, such as the number of delivered packets, the delivery delay and the number of transmissions. Unfortunately, in the context of opportunistic networks, these metrics are often highly correlated and usually conflicting. To make things worse, the characteristics of the network affect the importance of each metric as well as the levels of its correlation with other metrics. In this work, we first propose a set of performance evaluation metrics that are normalized with respect to the optimal performance. This approach tackles several of the above-mentioned shortcomings of traditional evaluation metrics. We then formulate the evaluation of routing protocols as a Multiple-Criteria Decision-Making (MCDM) problem where each routing protocol is an alternative and the performance metrics correspond to a set of criteria. We use this formulation to develop an evaluation framework that objectively ranks the performance of opportunistic routing protocols. To this end, we reshape well-known concepts and algorithms from the MCDM field to address the special requirements that are specific to the opportunistic context. We present detailed simulation results of well-known routing protocols in various opportunistic environments and rank their performance according to the proposed framework. In conclusion, no algorithm was able to achieve the best performance in all or the majority of the network topologies that we studied. This demonstrates the diversity of challenges that routing mechanisms face in such networks.
       
  • MRA: A modified reverse auction based framework for incentive mechanisms
           in mobile crowdsensing systems
    • Abstract: Publication date: Available online 3 June 2019Source: Computer CommunicationsAuthor(s): Samad Saadatmand, Salil S. Kanhere Mobile Crowdsensing (MCS) applications take advantage of the ubiquity and sensing power of smartphones in data gathering. Designing an incentive mechanism for motivating individuals to participate in such systems is vital. Reverse Auction (RA) is a popular framework in which first, the participants bid their expected returns, and then, the task creator selects a subset of them with a view to maximise the cumulative contribution within a prescribed budget. In RA, the participants are not aware of their winning probability before the auction is closed. If the participants are given some statistical information about the returns associated with their bid and contribution, they may reduce their bid and/or increase their contribution in order to increase their returns. In this paper, we propose Modified Reverse Auction (MRA) wherein, before the auction is closed, the winning probability of the participants are estimated and revealed individually, and then they are allowed to improve their winning probability by reducing their bid and/or increasing their contribution via moving to a different location. We also propose a tool called action evaluator which helps the participants to find their most profitable bid and/or location within certain specified limits. We also propose an enhancement called MRA with Profit Booster (MRA-PB), which employs a profit booster strategy to not only improve the profit of the participants who are amenable to following the recommendation of the action evaluator, but also to increase the total contribution, which benefits the task creator. Through conducting extensive experiments, we show that in comparison to RA, the MRA not only benefits the task creator by increasing the return on investment (i.e., the total contribution for the same budget), but also increases the total received rewards of the participants who follow the recommendation of the action evaluator during the auction.
       
  • Studying the evolution of content providers in IPv4 and IPv6 internet
           cores
    • Abstract: Publication date: Available online 3 June 2019Source: Computer CommunicationsAuthor(s): Esteban Carisimo, Carlos Selmo, J. Ignacio Alvarez-Hamelin, Amogh Dhamdhere There is recent evidence that the core of the Internet, which was formerly dominated by large transit providers, has been reshaped after the transition to a multimedia-oriented network, first by general-purpose CDNs and now by private CDNs. In this work we use k-cores, an element of graph theory, to define which ASes compose the core of the Internet and to track the evolution of the core since 1999. Specifically, we investigate whether large players in the Internet content and CDN ecosystem belong to the core and, if so, since when. In addition, we examine differences between the IPv4 and IPv6 cores. We further investigate regional differences in the evolution of large content providers. Finally, we show that the core of the Internet has incorporated an increasing number of content ASes in recent years. To enable reproducibility of this work, we provide a website to allow interactive analysis of our datasets to detect, for example, “up and coming” ASes using customized queries.
       
  • An online dynamic traffic matrix completion method in software defined
           networks
    • Abstract: Publication date: Available online 3 June 2019Source: Computer CommunicationsAuthor(s): Dongyang Li, Changyou Xing, Guomin Zhang, Huaping Cao, Bo Xu Online temporal Traffic Matrix (TM) estimation is important for network management and traffic engineering. However, current estimation methods are insufficient in estimation accuracy and measurement cost. In this paper, by combining the low rank feature of the traffic matrix and the flow measurement capability in Software Defined Networks (SDN), we propose a novel online dynamic temporal traffic matrix completion mechanism DTMC. DTMC evaluates the impact of different Origin-Destination (OD) flows on improving the traffic matrix estimation accuracy from the perspective of uncertainty and temporal stability, selects an appropriate number of “most-informative” flows to construct the measurement set, and finally recovers the complete traffic matrix by using the partially measured OD flow information dynamically. The experiment results on two Internet measurement datasets show that DTMC can estimate the dynamic temporal traffic matrix accurately only by consuming a small amount of measurement resources.
       
  • Maximizing mobiles energy saving through tasks optimal offloading
           placement in two-tier cloud: A theoretical and an experimental study
    • Abstract: Publication date: Available online 27 May 2019Source: Computer CommunicationsAuthor(s): Houssemeddine Mazouzi, Khaled Boussetta, Nadjib Achir In this paper, we focus on tasks offloading over two tiered mobile edge computing environment. We consider several users with energy constrained tasks that can be offloaded over edge clouds (cloudlets) or on a remote cloud with differentiated system and network resources capacities. We investigate offloading policy that decides which tasks should be offloaded and determine the offloading location on the cloudlets or on the cloud. The objective is to minimize the total energy consumed by the users. We formulate this problem as a Non-Linear Binary Integer Programming. Since the centralized optimal solution is NP-hard, we propose a distributed linear relaxation heuristic based on Lagrangian decomposition approach. To solve the subproblems, we also propose a greedy heuristic that computes the best cloudlet selection and bandwidth allocation following tasks’ energy consumption. We compared our proposal against existing approaches under different system parameters (CPU resources), variable number of users and for six applications, each having specific traffic pattern, resource demands and time constraints. Numerical results show that our proposal outperforms existing approaches. In addition to the theoretical approach, we evaluate our offloading policy using real experiments. In this case, we setup a real testbed composed of client terminal, offloading server located either at the edge or at a remote Cloud. We also implemented our proposal as an offloading middleware on both the client and the offloading server. Using this testbed, we were able to evaluate our offloading decision policy for multi-users context with three real Android OS applications, with different traffic patterns and resource demands. We also discuss the performance of our proposal for each application and we analyze the multi-users effect.
       
  • A delay-aware spectrum handoff scheme for prioritized time-critical
           industrial applications with channel selection strategy
    • Abstract: Publication date: Available online 27 May 2019Source: Computer CommunicationsAuthor(s): Stephen S. Oyewobi, Gerhard P. Hancke, Adnan M. Abu-Mahfouz, Adeiza J. Onumanyi Cognitive radio has emerged as an enabling technology in the realization of a spectrum-efficient and delay-sensitive industrial wireless communication where nodes are capable of responding in real-time. However, particularly for time-critical industrial applications, because of the link-varying channel capacity, the random arrival of a primary user (PU), and the significant delay caused by spectrum handoff (SH), it is challenging to realize a seamless real-time response which results in a quality of service (QoS) degradation. Therefore, the objectives of this paper is to increase spectrum utilization efficiency by allocating channel based on the priority of a user QoS requirements, to reduce SH delay, to minimize latency by preventing avoidable SHs, and to provide real-time response. To achieve an effective spectrum utilization, we proposed an integrated preemptive/non-preemptive priority scheme to allocate channels according to the priority of user QoS requirements. On the other hand, to avoid significant SH delays and substantial latency resulting from random PU arrival, a unified spectrum sensing technique was developed by integrating proactive sensing and the likelihood estimation technique to differentiate between a hidden and a co-existence PU, and to estimate the mean value of the busy and the idle periods of a channel respectively. Similarly, to prevent poor quality channel selection, a channel selection technique that jointly combines a reward system that uses metrics, e.g. interference range, and availability of a common channel to ranks a set of potential target channels, and a cost function that optimizes the probability of selecting the channel with the best characteristics as candidate channels for opportunistic transmission and for handoffs was developed. The simulation results show a significant performance gain of the delay-PritSHS in terms of number of SHs, Latency, as well as throughput for time-critical industrial applications in comparison to other schemes.
       
  • OpenCache: A lightweight regional cache collaboration approach in
           hierarchical-named ICN
    • Abstract: Publication date: Available online 23 May 2019Source: Computer CommunicationsAuthor(s): Yating Yang, Tian Song, Beichuan Zhang Information-centric networking (ICN) names contents instead of end-nodes and enables in-network caching to reuse those named packets, thus improving the efficiency of content delivery. On-path caching is an inherent feature in ICN, which caches contents along the path from providers to consumers, while off-path caching is not directly supported and its maintenance normally requires non-trivial overhead. In this paper, we propose a lightweight regional cache collaboration approach, called OpenCache, to sharing popular cached data among small-range caches with least cache information exchanges, especially for hierarchical-named ICN. Different from other available solutions, OpenCache enables collaborators to exchange aggregated hierarchical names (i.e., prefixes), instead of data structures summarized from separated and specific data names, to fundamentally reduce the collaborating cost of communication and maintenance. In addition, our approach exploits forwarding information base (FIB) to selectively relay Interest packets to nearby collaborative routers for low-cost data retrieval. Theoretical analyses and extensive experiments have been conducted to evaluate our scheme and the results show that OpenCache can reduce packet latency in retrieving data by about 38% compared to original ICN while its additional collaborating overhead is only around 15% of other schemes. Our approach explores the feasibility of lightweight collaboration with aggregation of hierarchical names.
       
  • Adaptive resource allocation based on the billing granularity in
           edge-cloud architecture
    • Abstract: Publication date: Available online 22 May 2019Source: Computer CommunicationsAuthor(s): Chunlin Li, Hezhi Sun, Hengliang Tang, Youlong Luo With the rapid development and popularization of the Internet of Things technology, the number of network edge devices has increased rapidly, and the Internet of Things perception layer has generated massive data. Cloud-Edge collaboration will be used more and more to solve this problem. When the business reaches its peak, cloud computing capabilities cannot meet business needs. The cloud service provider can apply for resources to meet the requirements of the computing resources. After the peak period of the business, if there are idle computing resources, the resources can be released to the cloud service provider, which can reduce the service cost and save the computing resources. The traditional flexible resource management is mainly used in a single cloud environment, and the prediction of the resource demand is insufficient. The factor of the cloud resource billing granularity is neglected, resulting in high cloud lease cost. Therefore, an adaptive resource allocation algorithm and a data migration algorithm are proposed. The prediction algorithm provides the basis for the adaptive resource allocation of the edge cloud cluster. The adaptive resource allocation algorithm determines the resource allocation scheme of the edge cloud cluster with the lowest service cost. The data migration algorithm guarantees the reliability of data and achieves cluster load balancing. A large number of experimental results show that our newly proposed algorithm can greatly improve system performance in terms of better cost control, higher data integrity and load balancing.
       
  • Prioritize efficiently: Layer selection in network coding
    • Abstract: Publication date: Available online 22 May 2019Source: Computer CommunicationsAuthor(s): Roman Naumann, Marie Schaeffer, Stefan Dietzel, Björn Scheuermann Network coding simplifies routing decisions, improves throughput, and increases tolerance against packet loss. A fundamental limitation, however, is delay: decoding requires as many independent linear combinations as data blocks. Prioritized network coding reduces this delay problem by introducing a hierarchy of prioritization layers. What remains is the problem of choosing a layer to approach two often-contradicting goals: reduce delay until prioritized layers can be decoded and keep the total number of transmissions low. In this paper, we propose an algorithm for this problem that – based on limited feedback – primarily minimizes per-layer delay but identifies opportunities to reduce the required transmissions when per-layer delay is unaffected. Our evaluation shows that our algorithm improves per-layer delay compared to hierarchical network coding and is close to the theoretical optimum number of total transmissions. Moreover, we demonstrate how the proposed algorithm can benefit smart-factory applications that operationalize delay-sensitive information from the production process.
       
  • Improved LTE like initial uplink synchronization via reduced problem
           dimension
    • Abstract: Publication date: Available online 21 May 2019Source: Computer CommunicationsAuthor(s): Md Mashud Hyder, Kaushik Mahata Initial uplink synchronization (IUS) is a random access process in LTE that enables the eNodeB to detect, and uplink synchronize new user equipment. In future networks with huge number of devices, the number of simultaneous IUS users will increase significantly. In addition, it is desirable to serve users moving at high speed. We exploit the structure of the physical random access channel (PRACH) in LTE to reduce the dimension of the underlying data model. This reduction gives a very compact representation of channel impulse response (CIR). We utilize this representation to develop an efficient algorithm which can work in presence of large multiple access interference (MAI) and high carrier frequency offsets (CFO). When compared with the state of the art methods. the proposed method is capable of detecting a significantly higher number of IUS users and can allow high values of CFO. In addition, it produces very reliable estimates of both CIR and CFO of the detected users.
       
  • Identifying IoT devices and events based on packet length from encrypted
           traffic
    • Abstract: Publication date: Available online 21 May 2019Source: Computer CommunicationsAuthor(s): Antônio J. Pinheiro, Jeandro de M. Bezerra, Caio A.P. Burgardt, Divanilson R. Campelo Recently, machine learning algorithms have been used to identify Internet of Things (IoT) devices and events. However, existing proposals may inspect the packet payload, what creates risks to IoT users’ privacy, and may use several features, increasing the computational complexity for traffic classification. In addition, existing techniques may also use complex mechanisms for extracting traffic characteristics, including the creation of vectors containing data from the Transmission Control Protocol (TCP) sessions. This paper proposes a solution that uses packet length statistics from encrypted traffic to characterize the behavior of IoT devices and events in a smart home scenario. The solution uses only the statistical mean, the standard deviation and the number of bytes transmitted over a one-second window, which can be extracted from the encrypted traffic, making the use of TCP vectors unnecessary. The solution identifies IoT devices and events, such as voice commands to smart assistants, and also distinguishes between IoT and non-IoT devices. The solution to characterize IoT devices and events is evaluated with traffic from two real-world testbeds and five classifiers. The evaluation included the algortihms k-Nearest Neighbors (k-NN), Decision Tree, Random Forest, Support Vector Machine (SVM) and Majority Voting, some of the most popular algorithms for traffic classification. The results show that the Random Forest algorithm can achieve up to 96% of accuracy in the identification of devices, 99% of precision in distinguishing between IoT and non-IoT devices and 99% of accuracy in the identification of IoT device events. Hypothesis testing is used to validate the obtained results. Also, the results show that the Decision Tree presented the lowest latency among the five classifiers evaluated in the identification of the devices, followed by k-NN, Random Forest, SVM and Majority Voting.
       
  • A windowing-based joint user pairing and resource allocation algorithm for
           V-MIMO systems
    • Abstract: Publication date: Available online 20 May 2019Source: Computer CommunicationsAuthor(s): Zhenyu Wang, Honglin Hu, Boqi Jia, Tianheng Xu In this paper, we investigate the user pairing and resource allocation (UP-RA) problem which is a critical step in uplink virtual multiple input multiple output (V-MIMO) systems. It becomes a joint problem under the framework of Long Term Evolution (LTE) where single carrier frequency division multiple access (SC-FDMA) is adopted in uplink due to the intrinsic consecutive resource allocation constraint imposed therein. Traditional two-step algorithms tackle this joint problem by separating the UP step and the RA step and turning them into two independent and successive procedures. Different from them, in this paper a windowing-based UP-RA algorithm is developed in which the user pairs are selected by maximizing their performance on a series of contiguous RBs rather than a single one as discussed in those traditional algorithms. With the windowing technique introduced in the new algorithm heuristically, improved performance in uplink V-MIMO systems can be achieved. In addition, we provide the relationship between the performance and the window size, and present that the window size can be selected adaptively to further exploit the diversity gain. Furthermore, to corroborate the universal validity of the proposed windowing technique, another algorithm named pairing and extension (P&E) is also modified accordingly by it. Corresponding simulation results manifest the great potential of the windowing technique to be applied to other general two-step algorithms in V-MIMO systems and improve their performances.
       
  • Speed based optimal power control in small cell networks
    • Abstract: Publication date: 15 June 2019Source: Computer Communications, Volumes 142–143Author(s): Veeraruna Kavitha, Manu K. Gupta, Véronique Capdevielle, Rahul Kishor M., Majed Haddad Small cell networks promise good quality of service (QoS) even for cell edge users, however pose challenges to cater to the high-speed users. The major difficulty being that of frequent handovers and the corresponding handover losses, which significantly depend upon the speed of the user. It was shown previously that the optimal cell size increases with speed. Thus, in scenarios with diverse users (speeds spanning over large ranges), it would be inefficient to serve all users using common cell radius and it is practically infeasible to design different cell sizes for different speeds. Alternatively, we propose to allocate power to a user based on its speed, e.g., higher power virtually increases the cell size. We solve well known Hamiltonian Jacobi equations under certain assumptions to obtain a power law, optimal for load factor and busy probability, for any given average power constraint and cell size. The optimal power control turns out to be linear in speed. We build a system level simulator for small cell network, using elaborate Monte-Carlo simulations, and show that the performance of the system improves significantly with linear power law. The power law is tested even for the cases, for which the system does not satisfy the assumptions required by the theory. For example, the linear power law has significant improvement in comparison with the ’equal power’ system, even in presence of time varying and random interference. We observe good improvement in almost all cases with improvements up to 89% for certain configurations.
       
  • Dynamic load balancing with tokens
    • Abstract: Publication date: Available online 17 May 2019Source: Computer CommunicationsAuthor(s): Céline Comte Efficiently exploiting the resources of data centers is a complex task that requires efficient and reliable load balancing and resource allocation algorithms. The former are in charge of assigning jobs to servers upon their arrival in the system, while the latter are responsible for sharing the server resources between their assigned jobs. These algorithms should adapt to various constraints, such as data locality, that restrict the feasible job assignments. In this paper, we propose a token-based algorithm that efficiently balances the load between the servers without requiring any knowledge on the job arrival rates and the server capacities. Assuming a balanced fair sharing of the server resources, we show that the resulting dynamic load balancing is insensitive to the job size distribution. Its performance is compared to that obtained under the best static load balancing and in an ideal system that would constantly optimize the resource utilization. We also make the connection with other token-based algorithms such as Join-Idle-Queue.
       
  • A survey of Internet of Things communication using ICN: A use case
           perspective
    • Abstract: Publication date: Available online 17 May 2019Source: Computer CommunicationsAuthor(s): Boubakr Nour, Kashif Sharif, Fan Li, Sujit Biswas, Hassine Moungla, Mohsen Guizani, Yu Wang Internet of Things (IoT) has gained extensive attention from industry and academia alike in past decade. The connectivity of each and every piece of technology in the environment with Internet, has opened many avenues of research and development. Applications, algorithms, trust models, devices, all have evolved to accommodate the demands of user needs in the most optimal way possible. However, one thing still remains constant: host-centric communication. It is the most predominant way of communication in Internet today. With evolution of everything else, host based communication has been stretched to limits, and exploration of new models have been underway for sometime. Information Centric Networking (ICN) is a major contender for the future Internet architecture, where content is the basic element regardless of its location (host). It intends to offer in-network caching, inherent mobility, multicast support, and content based security as part of design and not add-on functionality. In recent years, numerous efforts have been made to integrate IoT with ICN as the communication model. In this paper, we provide a detailed and systematic review of IoT-ICN research. We investigate ICN as communication enabler for IoT domain specific use cases, and the use of ICN features for the benefit of IoT networks. These include IoT device & content naming, discovery, and caching. We also survey synchronization, interoperability, publish/subscribe communication, quality of service, security, and mobility of IoT devices with ICN perspectives. The paper also presents challenges and possible research directions for the benefit of community.
       
  • TCP-NCL: A serialized-timer approach for enhancing TCP over heterogeneous
           wired/wireless networks
    • Abstract: Publication date: Available online 17 May 2019Source: Computer CommunicationsAuthor(s): Ka-Cheong Leung, Chengdi Lai, Huiyi Ding In heterogeneous wired/wireless networks, TCP performs unsatisfactorily since packet reordering and non-congestive losses may be falsely interpreted as congestive losses. This causes TCP to trigger fast retransmission and fast recovery spuriously, leading to under-utilization of available network resources. In this paper, we have developed a smart TCP sender (STS) model to differentiate congestive issues from the non-congestive ones for constructing more reliable signals of packet loss and network congestion over general error-prone channels. Two serialized timers are employed so that their expirations offer two separate signals of a packet loss and network congestion. The first timer is started when a packet is first injected into the network, and it will be cancelled if the acknowledgement is received. Otherwise, the packet will be retransmitted and the second timer is started upon the expiration of the first timer. The STS model is constructed based on the concept of minimizing expected cost and optimal setting of expiration periods for timer is determined. We have devised a novel TCP variant, known as TCP for non-congestive loss (TCP-NCL), as a practical approximation of the STS model. TCP-NCL can thus serve as a unified solution for effective congestion control, sequencing control, and loss recovery over wireless networks. The deployment of TCP-NCL requires modifications to sender-side TCP only, thereby facilitating possible future wide deployment. Our simulation studies show that TCP-NCL is robust against packet reordering as well as non-congestive packet loss while maintaining good responsiveness against congestive loss.
       
  • Performance estimation and evaluation framework for caching policies in
           hierarchical caches
    • Abstract: Publication date: Available online 15 May 2019Source: Computer CommunicationsAuthor(s): Eman Ramadan, Pariya Babaie, Zhi-Li Zhang The emergence of information-centric network (ICN) architectures has attracted a flurry of renewed research interest in caching policies and their performance analysis. One important feature ICNs offer that is distinct from classical computer caches is a distributed network of caches, namely, a cache network which poses additional challenges both in terms of practical cache management issues and performance analysis. Much attention of the research community has focused on performance analysis of cache networks under various caching policies. However, the issue of how to evaluate and compare caching policies for cache networks has not been adequately addressed. In this paper, we propose a novel and general framework for evaluating caching policies in a hierarchical network of caches. We introduce the notion of a hit probability/rate matrix, and employ a generalized notion of majorization as the basic tool for evaluating caching policies for various performance metrics. We discuss how the framework can be applied to existing caching policies, and conduct an extensive simulation-based evaluation to demonstrate the utility and accuracy of our framework.
       
  • GreenLoading: Using the citizens band radio for energy-efficient
           offloading of shared interests
    • Abstract: Publication date: Available online 14 May 2019Source: Computer CommunicationsAuthor(s): Pengfei Cui, Shu Chen, Joseph Camp Cellular networks are susceptible to being severely capacity-constrained during peak traffic hours or at special events such as sports and concerts. Many other applications are emerging for LTE and 5G networks that inject machine-to-machine (M2M) communications for Internet of Things (IoT) devices that sense the environment and react to diurnal patterns observed. Both for users and devices, the high congestion levels frequently lead to numerous retransmissions and severe battery depletion. However, there are frequently social cues that could be gleaned from interactions from websites and social networks of shared interest to a particular region at a particular time. Cellular network operators have sought to address these high levels of fluctuations and traffic burstiness via the use of offloading to unlicensed bands, which may be instructed by these social cues. In this paper, we leverage shared interest information in a given area to conserve power via the use of offloading to the emerging Citizens Broadband Radio Service (CBRS). Our GreenLoading framework enables hierarchical data delivery to significantly reduce power consumption and user fairness variation and includes a Broker Priority Assignment (BPA) algorithm to select data brokers for users. With the use of in-field measurements and web-based Google data across four diverse U.S. cities, we show an order of magnitude power savings via GreenLoading over a 24-hour period, on average, and power savings up to 97% at peak traffic times. Finally, we consider the role that a relaxation of wait times can play in the power efficiency of a GreenLoading network.
       
  • Network Service Orchestration: A survey
    • Abstract: Publication date: Available online 11 May 2019Source: Computer CommunicationsAuthor(s): Nathan F. Saraiva de Sousa, Danny A. Lachos Perez, Raphael V. Rosa, Mateus A.S. Santos, Christian Esteve Rothenberg Business models of network service providers are undergoing an evolving transformation fueled by vertical customer demands and technological advances such as 5G, Software Defined Networking (SDN), and Network Function Virtualization (NFV). Emerging scenarios call for agile network services consuming network, storage, and compute resources across heterogeneous infrastructures and administrative domains. Coordinating resource control and service creation across interconnected domains and diverse technologies becomes a grand challenge. Research and development efforts are being devoted to enabling orchestration processes to automate, coordinate, and manage the deployment and operation of network services. In this survey, we delve into the topic of Network Service Orchestration (NSO) by reviewing the historical background, relevant research projects, enabling technologies, and standardization activities. We define key concepts and propose a taxonomy of NSO approaches and solutions to pave the way towards a common understanding of the various ongoing efforts around the realization of diverse NSO application scenarios. Based on the analysis of the state of affairs, we present a series of open challenges and research opportunities, altogether contributing to a timely and comprehensive survey on the vibrant and strategic topic of network service orchestration.
       
  • Elastic-RAN: An adaptable multi-level elasticity model for cloud radio
           acess networks
    • Abstract: Publication date: Available online 8 May 2019Source: Computer CommunicationsAuthor(s): Rodrigo da Rosa Righi, Leandro Andrioli, Vinicius Facco Rodrigues, Cristiano André da Costa, Antonio Marcos Alberti, Dhananjay Singh Cellular mobile networks in 2020 will increase ten times their coverage area, with more than 50 billion connected devices. We will lead to a massive increase in data traffic, also fostering the development of 5G networks. Therefore industry and scientific initiatives have a crucial role in proposing related projects to meet such demand. Cloud Radio Access Networks (C-RANs) are gaining more and more attention in this context by adopting an architecture in which baseband units (BBUs) run into cloud computing resources, therefore taking advantage of distributed systems flexibility and cloud elasticity. One of the significant challenges in C-RANs lies in the high complexity of orchestrating computational resources to process incoming requests with both high performance and low infrastructure cost. In this regard, this article presents the Elastic-RAN model, which proposes a multi-level and adaptable elasticity for C-RANs. First, we explore the multi-level feature as follows: (i) one level for the BBU pools ( i.e., physical machines), given the high volume of traffic to particular BBU pools; (ii) another level for BBUs themselves (virtual machines) due to the high CPU and memory demands to process the incoming requests. Second, the adaptive feature refers to the moldable elasticity grain which resources in both previous levels are provisioned as close as possible to the current processing needs. We evaluated Elastic-RAN through experiments that simulated different load profiles, considering both CPU and network demands. We observed that Elastic-RAN might achieve gains up to 64% in the execution time when compared to a traditional C-RAN. Cellular network operators using the proposed technique will spend less energy and will have a solution that dynamically adjusts the baseband signal processing accordingly to the demand in their access networks.
       
  • Data offloading in cache-enabled cross-haul networks
    • Abstract: Publication date: Available online 6 May 2019Source: Computer CommunicationsAuthor(s): Haoran Mei, Huimin Lu, Limei Peng This paper studies a cache-enabled cross-haul network (Ce-XHaul) infrastructure under the banner of 5G, aiming at offloading data requests in the backhaul networks by means of extremely restricting the provisioning of user requests in the fronthaul networks. The major motivation behind Ce-XHaul is to install a proper amount of cache storage in base stations (BSs) or in helper devices that are deployed between BSs and user devices (UEs), so as to store the frequently requested files from users, which sequentially reduce the requirement of access to the distant backhaul networks. Specifically, we first numerically study the network performance of Ce-XHaul in terms of latency, say the average transmission end-to-end (E2E) delay, under three network scenarios that differ with each other in the caching capabilities, named as no-caching (scenario 1), caching-at-BSs (scenario 2), and caching-at-helper nodes (scenario 3), respectively. Then, we dedicate on scenario 2 and investigate the impact of caching capability of BSs on the average transmission E2E delay by proposing two integer linear programming (ILP) models. The two ILP models are designed based on routing algorithms that differ in the efforts made to restrict the data provisioning in the fronthaul. Numerical results show that the more caching capability in the fronthaul, the less the latency, nonetheless, with higher CAPEX cost being induced due to deployment of the cache storage and the additional helper nodes.
       
  • A solution to detect the existence of a malicious rogue AP
    • Abstract: Publication date: Available online 4 May 2019Source: Computer CommunicationsAuthor(s): Fu-Hau Hsu, Yu-Liang Hsu, Chuan-Sheng Wang A malicious rogue AP works like an evil twin; however, instead of using a good twin to connect to the Internet, a malicious rogue AP uses a 3G/4G mobile network to connect to the Internet. While administrators have sufficient information to distinguish rogue APs, it is difficult for client users to know whether they are using a wireless network with malicious an AP. To solve evil twin problems at client-side, many solutions make their detection based on some time metrics or evil twin features. However, time metrics may be influenced by pre-fetching, network topology, traffic volume, or network types. And the evil twin features such as packet forwarding cannot distinguish malicious rogue APs because they behave just like a legitimate AP. To solve above problem, this paper proposes an active user-side solution, called Wi-Fi Malicious Rogue AP Finder (RAF). RAF can be installed in any computer or laptop without any special requirement. RAF detect the existence of a malicious rogue AP based on different reverse traceroute information collected by a remote server. To the best of our knowledge, RAF is the first one client-side solution which could detect malicious rogue APs based on path information but not time metrics.
       
  • A comparison of web privacy protection techniques
    • Abstract: Publication date: Available online 4 May 2019Source: Computer CommunicationsAuthor(s): Johan Mazel, Richard Garnier, Kensuke Fukuda Tracking is pervasive on the web. Third party trackers acquire user data through information leak from websites, and user browsing history using cookies and device fingerprinting. In response, several privacy protection techniques (e.g. the Ghostery browser extension) have been developed. To the best of our knowledge, our work is the first study that proposes a reliable methodology for privacy protection comparison, and extensively compares a wide set of privacy protection techniques. Our contributions are the following. First, we propose a robust methodology to compare privacy protection techniques when crawling many websites, and quantify measurement error. To this end, we reuse the privacy footprint and apply the Kolmogorov–Smirnov test on browsing metrics. This test is likewise applied to HTML-based metrics to assess webpage quality degradation. To complement HTML-based metrics, we also design a manual analysis. Second, we study the overlap of blocking resources between most popular browser extensions, and compare the performances using the proposed methodology. We show that protection techniques have vastly different performances, and that the best of them exhibit a wide overlap. Next, we analyze the impact of privacy protection techniques on webpage quality. We show that automated HTML-based analysis sometimes fails to expose quality reduction perceived by users. Finally, we provide a set of usage recommendations for end-users and research recommendations for the scientific community. Ghostery and uBlock Origin provide the best trade-off between protection and webpage quality. Ghostery however requires a configuration step which is difficult for users. The RequestPolicy Continued and NoScript extensions exhibit the best performances but reduce webpage quality. Ghostery and uBlock Origin use manually built blocking lists which are cumbersome to maintain. Research efforts should focus on improving existing approaches that do not rely on blocking lists (such as Privacy badger or MyTrackingChoices), and automatically building reliable blocking lists.
       
  • A machine learning approach to evolving an optimal propagation model for
           last mile connectivity using low altitude platforms
    • Abstract: Publication date: Available online 11 April 2019Source: Computer CommunicationsAuthor(s): Faris A. Almalki, Marios C. Angelides This paper develops a machine leaning framework that evolves an optimal propagation model for the last mile with Low Altitude Platforms from existing propagation models. Existing propagation models reviewed exhibit both advantages and shortcomings in relation to a set of factors that affect performance across different terrains, i.e. path loss, elevation angle, altitude, coverage, power consumption, operational frequency, interference, and antenna type. A comparison of the predictions between the optimized and the existing models in relation to above set of factors reveals significant improvements are achieved with the optimal model.
       
 
 
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