Guangsheng Feng

Joint optimization of downlink and D2D transmissions for SVC streaming in cooperative cellular networks

Abstract We study the problem of broadcasting scalable video coded (SVC) streams in cellular networks, where all user equipments (UEs) require the same video content and cooperate with each other. To take the advantage of channel diversity gains, the base station (BS) uses network coding to generate linear combinations of video packets for broadcasting in the downlink. Once receiving sufficient number of the combinations, a UE can relay packets to others via device-to-device (D2D) connections. The optimal downlink and D2D transmission arrangement problem is formulated as a mixed integer non-linear programming (MINLP) problem, which becomes difficult to solve when the number of UEs increases. Then we convert the MINLP problem to a quasi-convex optimization problem using a continuous step function, and a primal-dual decomposition approach is used to solve it in a distributed way. In addition, we consider the influence of the transmission energy consumption to the optimal solution. Simulation results show that the proposed approach achieves near-optimal performance.

A Hybrid Reliable Heuristic Mapping Method Based on Survivable Virtual Networks for Network Virtualization

The reliable mapping of virtual networks is one of the hot issues in network virtualization researches. Unlike the traditional protection mechanisms based on redundancy and recovery mechanisms, we take the solution of the survivable virtual topology routing problem for reference to ensure that the rest of the mapped virtual networks keeps connected under a single node failure condition in the substrate network, which guarantees the completeness of the virtual network and continuity of services. In order to reduce the cost of the substrate network, a hybrid reliable heuristic mapping method based on survivable virtual networks (Hybrid-RHM-SVN) is proposed. In Hybrid-RHM-SVN, we formulate the reliable mapping problem as an integer linear program. Firstly, we calculate the primary-cut set of the virtual network subgraph where the failed node has been removed. Then, we use the ant colony optimization algorithm to achieve the approximate optimal mapping. The links in primary-cut set should select a substrate path that does not pass through the substrate node corresponding to the virtual node that has been removed first. The simulation results show that the acceptance rate of virtual networks, the average revenue of mapping, and the recovery rate of virtual networks are increased compared with the existing reliable mapping algorithms, respectively.

A Heuristic Indoor Path Planning Method Based on Hierarchical Indoor Modelling

Indoor path planning technology has become more and more extensive, e.g., indoor navigation and real-time scene construction. There are many difficulties in the existing indoor path planning researches, including the slower searching speed and the higher storage space cost, which is inability to meet user requirements in a complex indoor environment. This paper proposes a path planning method based on indoor maps. First, the indoor environment is hierarchically modelled, and then the corresponding path searching algorithm is developed to obtain the optimal path. Experimental results show that using the path planning method designed in this paper can effectively solve the above problems.

An effective method for service components selection based on micro-canonical annealing considering dependability assurance

Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service components. The best way to solve the problems in a distributed virtualized environment is dependable service components selection. Dependable service components selection can be modeled as finding a dependable service path, which is a multiconstrained optimal path problem. In this paper, a service components selection method that searches for the dependable service path in a distributed virtualized environment is proposed from the perspective of dependability assurance. The concept of Quality of Dependability is introduced to describe and constrain software system dependability during dynamic composition. Then, we model the dependable service components selection as a multiconstrained optimal path problem, and apply the Adaptive Bonus-Penalty Microcanonical Annealing algorithm to find the optimal dependable service path. The experimental results show that the proposed algorithm has high search success rate and quick converges.

DCAR: DTN Congestion Avoidance Routing Algorithm Based on Tokens in an Urban Environment

When a delay/disruption tolerant network (DTN) is applied in an urban scenario, the network is mainly composed of mobile devices carried by pedestrians, cars, and other vehicles, and the node’s movement trajectory is closely related to its social relationships and regular life; thus, most existing DTN routing algorithms cannot show efficient network performance in urban scenarios. In this paper, we propose a routing algorithm, called DCRA, which divides the urban map into grids; fixed sink stations are established in specific grids such that the communication range of each fixed sink station can cover a specific number of grids; these grids are defined as a cluster and allocated a number of tokens in each cluster; the tokens in the cluster are controlled by the fixed sink station. A node will transmit messages to a relay node that has a larger remaining buffer size and encounters fixed sink stations or the destination node more frequently after it obtains a message transmit token. Simulation experiments are carried out to verify the performance of the DCAR under an urban scenario, and results show that the DCAR algorithm is superior to existing routing algorithms in terms of delivery ratio, average delay, and network overhead.

Joint Optimization of Downlink and D2D Transmissions for SVC Streaming in Cooperative Cellular Networks

We study the problem of broadcasting scalable video coded (SVC) streams in cellular networks, where all user equipments (UEs) require the same video content and cooperate with each other. To take the advantage of channel diversity gains, the base station (BS) uses network coding to generate linear combinations of the video packets for broadcasting in the downlink. Once receiving sufficient number of the combinations, a UE can relay packets to others via device-to-device (D2D) connections. To optimize the downlink and D2D transmission arrangement, we first formulate a mixed integer non-linear programming (MINLP) problem, which becomes difficult to solve when the number of UEs increases. Then we convert the MINLP problem to a quasi-convex optimization problem using a continuous step function, and a primal-dual decomposition approach is used to solve it in a distributed way. Simulation results show that the proposed approach achieves a near-optimal solution.

MM-Sync: A Mobility Built-In Model Based Time Synchronization Approach for Underwater Sensor Networks

We study the problem of distributed time synchronization of underwater sensor networks, which is a quite challenging issue under such a dynamic scenario. Due to the high and varying transmission delay caused by the mobile network nodes, the existing works cannot achieve a desirable accuracy of synchronization. To overcome this problem, a mobility built-in model is firstly explored for the time synchronization in consideration of the effect of mobility and transmission delay. Then, a time synchronization equation is formulated according to the proposed model. Based on the equation, a mobility built-in model based time synchronization algorithm, namely MM-sync, is designed. The experiment results show that MM-sync cannot only reduce the consumption of energy, but also achieve a higher accuracy than state-of-art solutions.