Xinchen Lyu, Wei Ni, Hui Tian, R. Liu, Xin Wang, G. Giannakis, A. Paulraj
{"title":"Optimal Schedule of Mobile Edge Computing for Internet of Things Using Partial Information","authors":"Xinchen Lyu, Wei Ni, Hui Tian, R. Liu, Xin Wang, G. Giannakis, A. Paulraj","doi":"10.1109/JSAC.2017.2760186","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760186","url":null,"abstract":"Mobile edge computing is of particular interest to Internet of Things (IoT), where inexpensive simple devices can get complex tasks offloaded to and processed at powerful infrastructure. Scheduling is challenging due to stochastic task arrivals and wireless channels, congested air interface, and more prominently, prohibitive feedbacks from thousands of devices. In this paper, we generate asymptotically optimal schedules tolerant to out-of-date network knowledge, thereby relieving stringent requirements on feedbacks. A perturbed Lyapunov function is designed to stochastically maximize a network utility balancing throughput and fairness. A knapsack problem is solved per slot for the optimal schedule, provided up-to-date knowledge on the data and energy backlogs of all devices. The knapsack problem is relaxed to accommodate out-of-date network states. Encapsulating the optimal schedule under up-to-date network knowledge, the solution under partial out-of-date knowledge preserves asymptotic optimality, and allows devices to self-nominate for feedback. Corroborated by simulations, our approach is able to dramatically reduce feedbacks at no cost of optimality. The number of devices that need to feed back is reduced to less than 60 out of a total of 5000 IoT devices.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2606-2615"},"PeriodicalIF":16.4,"publicationDate":"2017-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44488507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jun Du, E. Gelenbe, Chunxiao Jiang, Haijun Zhang, Yong Ren
{"title":"Contract Design for Traffic Offloading and Resource Allocation in Heterogeneous Ultra-Dense Networks","authors":"Jun Du, E. Gelenbe, Chunxiao Jiang, Haijun Zhang, Yong Ren","doi":"10.1109/JSAC.2017.2760459","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760459","url":null,"abstract":"In heterogeneous ultra-dense networks (HetUDNs), the software-defined wireless network (SDWN) separates resource management from geo-distributed resources belonging to different service providers. A centralized SDWN controller can manage the entire network globally. In this paper, we focus on mobile traffic offloading and resource allocation in SDWN-based HetUDNs, constituted of different macro base stations and small-cell base stations (SBSs). We explore a scenario where SBSs’ capacities are available, but their offloading performance is unknown to the SDWN controller: this is the information asymmetric case. To address this asymmetry, incentivized traffic offloading contracts are designed to encourage each SBS to select the contract that achieves its own maximum utility. The characteristics of large numbers of SBSs in HetUDNs are aggregated in an analytical model, allowing us to select the SBS types that provide the off-loading, based on different contracts which offer rationality and incentive compatibility to different SBS types. This leads to a closed-form expression for selecting the SBS types involved, and we prove the monotonicity and incentive compatibility of the resulting contracts. The effectiveness and efficiency of the proposed contract-based traffic offloading mechanism, and its overall system performance, are validated using simulations.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2457-2467"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760459","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49148816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Distributed Locality-Sensitive Hashing-Based Approach for Cloud Service Recommendation From Multi-Source Data","authors":"Lianyong Qi, Xuyun Zhang, Wanchun Dou, Q. Ni","doi":"10.1109/JSAC.2017.2760458","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760458","url":null,"abstract":"To maximize the economic benefits, a cloud service provider needs to recommend its services to as many users as possible based on the historical user-service quality data. However, when a cloud platform (e.g., Amazon) intends to make a service recommendation decision, considering only its own user-service quality data is insufficient, because a cloud user may invoke services from multiple distributed cloud platforms (e.g., Amazon and IBM). In this situation, it is promising for Amazon to collaborate with other cloud platforms (e.g., IBM) to utilize the integrated data for the service recommendation to improve the recommendation accuracy. However, two challenges are present in the above-mentioned collaboration process, where we attempt to use multi-source data for the service recommendation. First, protecting users’ privacy is challenging when IBM releases its own data to Amazon. Second, the recommendation efficiency and scalability are often low when the user-service quality data of Amazon and IBM update frequently. Considering these challenges, a privacy-preserving and scalable service recommendation approach based on distributed locality-sensitive hashing, i.e., $textit {SerRec}_{textit {distri-LSH}}$ , is proposed in this paper to handle the service recommendation in a distributed cloud environment. Extensive experiments on the WS-DREAM data set validate the feasibility of our approach in terms of service recommendation accuracy, scalability, and privacy preservation.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2616-2624"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760458","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41795108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Z. Yousaf, M. Bredel, S. Schaller, Fabian Schneider
{"title":"NFV and SDN—Key Technology Enablers for 5G Networks","authors":"F. Z. Yousaf, M. Bredel, S. Schaller, Fabian Schneider","doi":"10.1109/JSAC.2017.2760418","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760418","url":null,"abstract":"Communication networks are undergoing their next evolutionary step toward 5G. The 5G networks are envisioned to provide a flexible, scalable, agile, and programmable network platform over which different services with varying requirements can be deployed and managed within strict performance bounds. In order to address these challenges, a paradigm shift is taking place in the technologies that drive the networks, and thus their architecture. Innovative concepts and techniques are being developed to power the next generation mobile networks. At the heart of this development lie Network Function Virtualization and Software Defined Networking technologies, which are now recognized as being two of the key technology enablers for realizing 5G networks, and which have introduced a major change in the way network services are deployed and operated. For interested readers that are new to the field of SDN and NFV, this paper provides an overview of both these technologies with reference to the 5G networks. Most importantly, it describes how the two technologies complement each other and how they are expected to drive the networks of near future.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2468-2478"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45349504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Syed Noor-ul-Hassan Shirazi, Antonios Gouglidis, Arsham Farshad, D. Hutchison
{"title":"The Extended Cloud: Review and Analysis of Mobile Edge Computing and Fog From a Security and Resilience Perspective","authors":"Syed Noor-ul-Hassan Shirazi, Antonios Gouglidis, Arsham Farshad, D. Hutchison","doi":"10.1109/JSAC.2017.2760478","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760478","url":null,"abstract":"Mobile edge computing (MEC) and fog are emerging computing models that extend the cloud and its services to the edge of the network. The emergence of both MEC and fog introduce new requirements, which mean their supported deployment models must be investigated. In this paper, we point out the influence and strong impact of the extended cloud (i.e., the MEC and fog) on existing communication and networking service models of the cloud. Although the relation between them is fairly evident, there are important properties, notably those of security and resilience, that we study in relation to the newly posed requirements from the MEC and fog. Although security and resilience have been already investigated in the context of the cloud-to a certain extent-existing solutions may not be applicable in the context of the extended cloud. Our approach includes the examination of models and architectures that underpin the extended cloud, and we provide a contemporary discussion on the most evident characteristics associated with them. We examine the technologies that implement these models and architectures, and analyze them with respect to security and resilience requirements. Furthermore, approaches to security and resilience-related mechanisms are examined in the cloud (specifically, anomaly detection and policy-based resilience management), and we argue that these can also be applied in order to improve security and achieve resilience in the extended cloud environment.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2586-2595"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44025503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"HYPER: A Hybrid High-Performance Framework for Network Function Virtualization","authors":"Chen Sun, J. Bi, Zhilong Zheng, Hongxin Hu","doi":"10.1109/JSAC.2017.2760438","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760438","url":null,"abstract":"Network function virtualization (NFV) offers the potential for both enhancing service delivery flexibility and reducing overall costs by virtualizing network functions that are traditionally implemented in dedicated hardware. However, the flexibility of NFV comes with considerable compromises since virtual machine carried functions could introduce significant performance overhead. In this paper, we present a novel high-performance framework called HYPER, which combines programmable hardware infrastructure and traditional software infrastructure in NFV to achieve both high performance and flexibility for supporting virtualized network functions (VNFs). In HYPER, we design a mediator layer to hide underlying infrastructure heterogeneity from the NFV orchestrator to simplify VNF management. In addition, we design a SLA-aware service chaining algorithm in HYPER to leverage the benefits of the hybrid infrastructure to fulfill both functional and performance requirements from service subscribers (or tenants). To optimize resource utilization efficiency, we also introduce a performance-aware VNF placement algorithm in HYPER, which accommodates both resource and performance requirements in placing VNFs. We implement HYPER in a testbed based on OpenStack and ONetCard. Experimental results show that HYPER reduces the forwarding latency of a service chain by 40% to 67% compared with data plane development kit -based implementation, while maintaining the flexibility of VNF management.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2490-2500"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760438","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44491092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pengzhan Wang, Hongli Xu, Liusheng Huang, Jie He, Zeyu Meng
{"title":"Control Link Load Balancing and Low Delay Route Deployment for Software Defined Networks","authors":"Pengzhan Wang, Hongli Xu, Liusheng Huang, Jie He, Zeyu Meng","doi":"10.1109/JSAC.2017.2760187","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760187","url":null,"abstract":"Software defined networking (SDN) separates the data plane and control plane on independent devices. Since the data plane, consisting of switches, is responsible for packets forwarding, previous work often considers the different constraints (e.g., data link capacity and flow-table size) only in the data plane to provide better QoS for users. However, due to limited CPU processing power and low speed of flow-table updating on each switch, the control channels/links between switches and the controller often have very limited capacity, which will cause QoS performance (e.g., response time and throughput) degradation when the switch should handle a high traffic load. The goal of our paper is to achieve better QoS by jointly considering the control link constraint and other different constraints of the data plane in SDNs. We formally define the control link load balancing and low delay route deployment problems, and prove the NP-Hardness. We present two algorithms with bounded approximation factors for each problem and implement the proposed methods on our SDN testbed. Extensive simulation results and experimental results show that our algorithms can reduce control link load by about 50% and response time by about 60%, and increase the network throughput by 65% compared with previous methods.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2446-2456"},"PeriodicalIF":16.4,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48019865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"QoS-Aware and Reliable Traffic Steering for Service Function Chaining in Mobile Networks","authors":"Ruozhou Yu, G. Xue, Xiang Zhang","doi":"10.1109/JSAC.2017.2760158","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760158","url":null,"abstract":"The ever-increasing mobile traffic has inspired deployment of capacity and performance enhancing network services within mobile networks. Owing to recent advances in network function virtualization, such network services can be flexibly and cost-efficiently deployed in the mobile network as software components, avoiding the need for costly hardware deployment. Nevertheless, this complicates network planning by bringing the need for service function chaining. In this paper, we study mobile network planning through a software-defined approach, considering both quality-of-service and reliability of different classes of traffic. We define and formulate the traffic steering problem for service function chaining in mobile networks, which turns out to be $mathcal {NP}$ -hard. We then develop a fast approximation scheme for the problem, and evaluate its performance via extensive simulation experiments. The results show that our algorithm is near-optimal, and achieves much better performance compared with baseline algorithms.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2522-2531"},"PeriodicalIF":16.4,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760158","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47037388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cooperative Edge Caching in Software-Defined Hyper-Cellular Networks","authors":"Qiang Li, Wennian Shi, Xiaohu Ge, Z. Niu","doi":"10.1109/JSAC.2017.2760184","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760184","url":null,"abstract":"In this paper, content caching is considered in a software-defined hyper-cellular network (SD-HCN) with capacity-limited backhaul connections. To achieve efficient content caching and delivery at the network edge, an analytical framework of minimizing the average content provisioning cost of SD-HCN, e.g., latency, bandwidth, and so on, is first formulated subjected to a sum storage capacity constraint. An optimal solution to this problem requires a joint design of storage allocation and content placement at the centralized control base station (CBS) and distributed traffic base stations (TBSs), which is NP-hard in general. To provide insights, a baseline non-cooperative caching strategy is first introduced between the CBS and TBSs. Then, an efficient cooperative edge caching strategy is proposed by leveraging the vertical cooperation between the CBS and TBSs, and horizontal cooperation between the TBSs. Analytical results demonstrate that the content provisioning cost of SD-HCN is significantly reduced by using the analytically obtained optimal storage allocation between the CBS and TBSs, and the proposed cooperative edge caching strategy always outperforms the non-cooperative caching strategy. Furthermore, by switching between the vertical and horizontal cooperative caching modes, extra performance gains can be achieved by the proposed cooperative edge caching strategy.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2596-2605"},"PeriodicalIF":16.4,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43796985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stemflow: Software-Defined Inter-Datacenter Overlay as a Service","authors":"Shuhao Liu, Baochun Li","doi":"10.1109/JSAC.2017.2760159","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760159","url":null,"abstract":"Modern Internet applications are typically hosted in the public cloud, with multiple server instances running within geographically distributed datacenters. Thanks to the abundantly available bandwidth on wide-area links that interconnect these datacenters, it is conceivable that bandwidth-intensive applications may improve their performance by relaying their traffic through such an inter-datacenter network. However, there does not yet exist a cloud service that provides a turn-key solution to tap into such available bandwidth resources conveniently. In this paper, we design and implement Stemflow, a new system framework that provides Inter-Datacenter Overlay as a Service based on the software-defined networking principle. It offers an attractive foundation that helps an Internet application to transparently improve its scalability and performance by using inter-datacenter networks for its traffic. With Stemflow, all deployed server instances will construct an overlay atop an inter-datacenter network, and the routing decisions to relay application traffic are made by a centralized controller. The algorithms needed to make these decisions are customized to meet the needs of individual applications, and are cached within the data plane. We motivate and describe the design decisions, and present an extensive experimental evaluation in public cloud infrastructures, using two example applications as our case studies.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2563-2573"},"PeriodicalIF":16.4,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760159","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44255848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}