Network lifetime optimization for wireless video sensor networks with network coding/ARQ hybrid adaptive error-control scheme

Jointly optimal utility distortion-robustness and lifetime tradeoff for multimedia networks

“…The distortion-robustness sub-problem from (11) is given by 3 The objective function ϑ(ω s ) in (12) modulates the distortionrobustness to achieve the tradeoff with network lifetime. To achieve this tradeoff optimally, an appropriate choice of the objective function ϑ(ω s ) is required.…”

“…In [2], flow control optimization with lifetime constraint is considered. In another related work, performance optimization for wireless video networks to achieve resource allocation along with network lifetime maximization is considered in [3]. The authors in [4], have proposed power minimized rate allocation scheme (PMRAS) for multi-homed video scenario, where the objective is to perform optimal rate allocation while guaranteeing minimal total power consumption.…”

Energy and life time efficient enriched LEAR and APR with hybrid ARQ in wireless video sensor networks

“…Wireless video sensor networks have been used for wild range applications such as security, monitoring purpose, emergency response, environmental tracking and health monitoring. Battery powered sensors are often deployed in the remote and unreachable locations [1].Therefore, minimizing power and providing high quality video are of main importance in wireless video sensor networks. An important challenges in wireless video sensor network is high energy consumption, since the insufficiency of energy has direct impact on the coverage, it is not possible to have all the sensor node activity at the same time.…”

Compressive network coding for wireless sensor networks: Spatio-temporal coding and optimization design

“…Tan et al in [18] maximized the network lifetime by optimizing the network flow control and video encoding bit rate jointly. The main goal of works [19][20] is to minimize the network energy consumption.…”

“…Currently, the existing works on optimization of NC-based network resource mainly address the problems of achieving the maximum throughput [16][17], the maximum lifetime [18], the minimum energy consumption [19][20], the minimum packet delay [21] and the tradeoff between two randomly former metrics [22][23][24].…”