<![CDATA[ IEEE/ACM Transactions on Networking - new TOC ]]>
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TOC Alert for Publication# 90 2018March 22<![CDATA[Table of contents]]>261C12522<![CDATA[IEEE/ACM Transactions on Networking publication information]]>261C2C279<![CDATA[Toward Cloud-Based Distributed Interactive Applications: Measurement, Modeling, and Analysis]]>2613163285<![CDATA[Not All VANET Broadcasts Are the Same: Context-Aware Class Based Broadcast]]>26117301993<![CDATA[A Probabilistic Framework for Structural Analysis and Community Detection in Directed Networks]]>26131462834<![CDATA[On the Rate Regions of Single-Channel and Multi-Channel Full-Duplex Links]]>26147602223<![CDATA[Asynchronously Coordinated Multi-Timescale Beamforming Architecture for Multi-Cell Networks]]>26161754602<![CDATA[Optimizing Internet Transit Routing for Content Delivery Networks]]>26176893378<![CDATA[Every Timestamp Counts: Accurate Tracking of Network Latencies Using Reconcilable Difference Aggregator]]>261901032086<![CDATA[SSED: Servers Under Software-Defined Network Architectures to Eliminate Discovery Messages]]>2611041173685<![CDATA[Boolean Gossip Networks]]>16 - 1 possible nonempty sets of binary Boolean functions, whether the induced chain is absorbing has nothing to do with the topology of the underlying interaction graph, as long as connectivity is assumed. These results illustrate the possibilities of relating dynamical properties of Boolean networks to graphical properties of the underlying interactions.]]>2611181302491<![CDATA[Anomaly Detection and Attribution in Networks With Temporally Correlated Traffic]]>2611311443086<![CDATA[Diamond: Nesting the Data Center Network With Wireless Rings in 3-D Space]]>2611451605094<![CDATA[One More Tag Enables Fine-Grained RFID Localization and Tracking]]>2611611743090<![CDATA[Spatial Mappings for Planning and Optimization of Cellular Networks]]>2611751882359<![CDATA[Easy Path Programming: Elevate Abstraction Level for Network Functions]]>2611892022327<![CDATA[Using Adaptive Heartbeat Rate on Long-Lived TCP Connections]]>2612032162494<![CDATA[Partial Order Theory for Fast TCAM Updates]]>2612172302181<![CDATA[Multi-Touch in the Air: Concurrent Micromovement Recognition Using RF Signals]]>2612312442643<![CDATA[Utility-Centric Networking: Balancing Transit Costs With Quality of Experience]]>2612452583031<![CDATA[Trading Utility for Privacy in Shared Spectrum Access Systems]]>2612592731790<![CDATA[Joint Resource Allocation for Software-Defined Networking, Caching, and Computing]]>2612742874129<![CDATA[Adaptive Sector Coloring Game for Geometric Network Information-Based Inter-Cell Interference Coordination in Wireless Cellular Networks]]>2612883013249<![CDATA[Cache Policies for Linear Utility Maximization]]>2613023131234<![CDATA[Radiation Constrained Scheduling of Wireless Charging Tasks]]>2613143272663<![CDATA[Loop-Free Route Updates for Software-Defined Networks]]>2613283412250<![CDATA[Priority Queueing for Packets With Two Characteristics]]>2613423551937<![CDATA[WMGR: A Generic and Compact Routing Scheme for Data Center Networks]]>2613563693256<![CDATA[Device-to-Device Networking Meets Cellular via Network Coding]]>2613703832204<![CDATA[Fast Rerouting Against Multi-Link Failures Without Topology Constraint]]>2613843971656<![CDATA[Scalability and Satisfiability of Quality-of-Information in Wireless Networks]]>scalably feasible QoI regions, which provide upper bounds on QoI requirements that can be supported for certain network applications.]]>2613984113249<![CDATA[On Practical Construction of Quality Fault-Tolerant Virtual Backbone in Homogeneous Wireless Networks]]>2614124212421<![CDATA[Kraken: Online and Elastic Resource Reservations for Cloud Datacenters]]>2614224353202<![CDATA[Scheduling Frameworks for Cloud Container Services]]>2614364501856<![CDATA[The Throughput and Access Delay of Slotted-Aloha With Exponential Backoff]]>2614514641663<![CDATA[FDoF: Enhancing Channel Utilization for 802.11ac]]>2614654772155<![CDATA[Information Spreading Forensics via Sequential Dependent Snapshots]]>independent observations of the underlying network while assuming a homogeneous information spreading rate. We conduct a theoretical and experimental study on information spreading, and propose a new and novel estimation framework to estimate 1) information spreading rates, 2) start time of the information source, and 3) the location of information source by utilizing multiple sequential and dependent snapshots where information can spread at heterogeneous rates. Our framework generalizes the current state-of-the-art rumor centrality [1] and the union rumor centrality [2]. Furthermore, we allow heterogeneous information spreading rates at different branches of a network. Our framework provides conditional maximum likelihood estimators for the above three metrics and is more accurate than rumor centrality and Jordan center in both synthetic networks and real-world networks. Applying our framework to the Twitter’s retweet networks, we can accurately determine who made the initial tweet and at what time the tweet was sent. Furthermore, we also validate that the rates of information spreading are indeed heterogeneous among different parts of a retweet network.]]>2614784912094<![CDATA[Scheduling of Collaborative Sequential Compressed Sensing Over Wide Spectrum Band]]>2614925051746<![CDATA[Optimal Control for Generalized Network-Flow Problems]]>virtual network of queues. When specialized to the unicast setting, the UMW policy yields a throughput-optimal cycle-free routing and link scheduling policy. This is in contrast with the well-known throughput-optimal back-pressure (BP) policy which allows for packet cycling, resulting in excessive latency. Extensive simulation results show that the proposed UMW policy incurs a substantially smaller delay as compared with the BP policy. The proof of throughput-optimality of the UMW policy combines ideas from the stochastic Lyapunov theory with a sample path argument from adversarial queueing theory and may be of independent theoretical interest.]]>2615065191373<![CDATA[SCAPE: Safe Charging With Adjustable Power]]>$R_{t}$ . We present novel techniques to reformulate SCAPE into a traditional linear programming problem, and then remove its redundant constraints as much as possible to reduce computational effort. Next, we propose a series of distributed algorithms, including a fully distributed algorithm that provably achieves $(1-epsilon)$ approximation ratio and requires only communications with neighbors within a constant distance for each charger. Through extensive simulation and testbed experiments, we demonstrate that our proposed algorithms can outperform the set-cover algorithm by up to 17.05%, and has an average performance gain of 41.1% over the existing algorithm in terms of the overall charging utility.]]>2615205332388<![CDATA[Dynamic, Fine-Grained Data Plane Monitoring With Monocle]]>2615345471741<![CDATA[Caching Encrypted Content Via Stochastic Cache Partitioning]]>2615485612424<![CDATA[Minimizing Controller Response Time Through Flow Redirecting in SDNs]]>2615625752227<![CDATA[Analysis of Millimeter-Wave Multi-Hop Networks With Full-Duplex Buffered Relays]]>2615765902996<![CDATA[Online Aggregation of the Forwarding Information Base: Accounting for Locality and Churn]]>2615916041689<![CDATA[An LDPC Approach for Chunked Network Codes]]>2616056171242<![CDATA[Achieving High Scalability Through Hybrid Switching in Software-Defined Networking]]>2616186322540<![CDATA[Joint Optimization of Multicast Energy in Delay-Constrained Mobile Wireless Networks]]>2616336463759<![CDATA[List of Reviewers]]>261647655101<![CDATA[IEEE/ACM Transactions on Networking society information]]>261C3C3169<![CDATA[IEEE/ACM Transactions on Networking information for authors]]>261C4C452