Junyu Lin

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.

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.

Design and Realization of an Indoor Positioning Algorithm Based on Differential Positioning Method

Nowadays, with the rapid development of location based services, the indoor positioning technology has become a hot research topic. In order to eliminate interference factors of indoor wireless signal propagation and improve the accuracy adaptability of indoor location, we design and implement an indoor location algorithm based on differential signal strength method. We reduce the effect of the fluctuation of wireless signal and improve the signal stability by using the first order difference method to deal with the collected signal strength parameters. According to small scale multipath effects of wireless signals are approximately equal in the same environment, we combine difference localization theory and plane geometric method to get the indoor target’s position. Our positioning algorithm can adapt to various indoor location technology and has good compatibility.

Optimizing broadcast duration for layered video streams in cellular networks

We study the layered video transmission optimization problem in the cellular networks, in which all User Equipments (UEs) require the same video content simultaneously via the cellular downlink transmission from the Base Station (BS) and Device-to-Device (D2D) transmission from other UEs. First, we propose a probability-based framework for each video layer to measure the video playback quality in terms of the outage probability. Next, the layered video transmission optimization problem is formulated as a Peak Signal-to-Noise Ratio (PSNR) loss minimization problem, which is then converted to an unmatured probability minimization problem by adding a differentiation weight on each layer based on its importance to the playback quality. In addition, we prove the formulated problem to be a log-convex optimization problem. Finally, we conduct extensive simulations to show that the proposed approach achieves the optimal allocation of the broadcast duration for each layer under various network conditions.

DGTM:a dynamic grouping based trust model for mobile peer-to-peer networks

The special characteristics of the mobile environment, such as limited bandwidth, dynamic topology, heterogeneity of peers, and limited power, pose additional challenges on mobile peer-to-peer (MP2P) networks. Trust management becomes an essential component of MP2P networks to promote peer transactions. However, in an MP2P network, peers frequently join and leave the network, which dynamically changes the network topology. Thus, it is difficult to establish long-term and effective trust relationships among peers. In this paper, we propose a dynamic grouping based trust model (DGTM) to classify peers. A group is formed according to the peers’ interests. Within a group, mobile peers share resources and tend to keep stable trust relationships. We propose three peer roles (super peers, relay peers, and ordinary peers) and two novel trust metrics (intragroup trust and intergroup trust). The two metrics are used to accurately measure the trust between two peers from the same group or from different groups. Simulations illustrate that our proposed DGTM always achieves the highest successful transaction rate and the best communication overhead under different circumstances.

Performance analysis and optimization for chunked network coding based wireless cooperative downloading systems

Dense network coding (NC) is widely used in wireless cooperative downloading systems. Wireless devices have limited computing resources. Researchers have recently found that dense NC is not suitable because of its high coding complexity, and it is necessary to use chunked NC in wireless environments. However, chunked NC can cause more communications, and the amount of communications is affected by the chunk size. Therefore, setting a suitable chunk size to improve the overall perfor-mance of chunked NC is a prerequisite for applying it in wireless cooperative downloading systems. Most of the existing studies on chunked NC focus on centralized wireless broadcasting systems, which are different from wireless cooperative downloading systems with distributed features. Accordingly, we study the performance of chunked NC based wireless cooperative downloading systems. First, an analysis model is established using a Markov process taking the distributed features into consideration, and then the block collection completion time of encoded blocks for cooperative downloading is optimized based on the analysis model. Furthermore, queuing theory is used to model the decoding process of the chunked NC. Combining queuing theory with the analysis model, the decoding completion time for cooperative downloading is optimized, and the optimal chunk size is derived. Numerical simulation shows that the block collection completion time and the decode completion time can be largely reduced after optimization.

Optimal transmission for scalable video coded streaming in cellular wireless networks with the cooperation of local peer-to-peer network

We study the problem of transmitting scalable video coded streams in a hybrid scenario including a global cellular network and a local peer-to-peer network. Given desirable channel condition in cellular downlink, some cellular user equipments can fetch the video chunks via the cellular base station directly, and also provide relay service via the local peer-to-peer network for other user equipments unable to meet their basic video quality. To take the advantage of channel diversity gains, the method of random linear coding is adopted to generate linear combinations of the video chunks for transmission in both the cellular and peer-to-peer networks. To optimize the cellular and peer-to-peer transmission arrangement, we first formulate it as a mixed integer nonlinear programming problem, which becomes more complicated when the number of user equipments increases. Then, we convert it to a quasi-convex optimization problem by approximating the indicator function with a continuous step function, and it can be solved by a centralized approach. Furthermore, a primal-dual decomposition approach is developed and a distributed algorithm is proposed accordingly. Simulation results show that the proposed approach achieves a near-optimal solution.

A Cooperative Optimization Method for Mobile User Data Offloading

We study the problem of mobile data offloading in a cooperative cellular network where the cellular network can offload a fraction of data traffic to its cooperative WiFi networks. To measure the metric of user satisfaction towards offloading scheme, an S-shaped function is introduced to capture the user utility, namely, the user satisfaction function. Therefore, the first objective is to maximize the user satisfaction. Considering the cooperation and competition among cellular and WiFi networks, the operator has to given up partial benefit to the cooperative partners. Therefore, optimal pricing is the other consideration of this work. The mobile data offloading problem is formulated as a joint optimization of “min-max” problem, which is converted into a bi-level optimization problem, where the upper level is to minimize the operator benefit loss and the lower one is to maximize the user satisfaction. Simulation results show that the proposed method achieves the near-optimal solutions with limited iterations.

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.

Multi-focus Image Fusion via Region Mosaicing on Contrast Pyramids

This paper proposes a new approach called region mosaicing on contrast pyramids for multi-focus image fusion. A density-based region growing is developed to construct a focused region mask for multi-focus images. The segmented focused region mask is decomposed into a mask pyramid, which is then used for supervised region mosaicing on a contrast pyramid. In this way, the focus measurement and the continuity of focused regions are incorporated and the pixel level pyramid fusion is improved at the region level. Objective and subjective experiments show that the proposed region mosaicing on contrast pyramids approach is more robust to noise and can fully preserves the focus information of the multi-focus images, reducing distortions of the fused images.