Routing versus energy optimization in a linear network

In wireless networks, devices (or nodes) often have a limited battery supply to use for the sending and reception of transmissions. By allowing nodes to relay messages for other nodes, the distance that needs to be bridged can be reduced, thus limiting the energy needed for a transmission. However, the number of transmissions a node needs to perform increases, costing more energy. Defining the lifetime of the network as the time until the first node depletes its battery, we investigate the impact of routing choices on the lifetime. In particular we focus on a linear network with nodes sending messages directly to all other nodes, or using full routing where transmissions are only sent to neighbouring nodes. We distinguish between networks with nodes on a grid or uniformly distributed and with full or random battery supply. Using simulation we validate our analytical results and discuss intermediate options for relaying of transmissions

Performance Analysis of Hierarchical Routing Protocols in Wireless Sensor Networks

This work focusses on analyzing the optimization strategies of routing protocols with respect to energy utilization of sensor nodes in Wireless Sensor Network (WSNs). Different routing mechanisms have been proposed to address energy optimization problem in sensor nodes. Clustering mechanism is one of the popular WSNs routing mechanisms. In this paper, we first address energy limitation constraints with respect to maximizing network life time using linear programming formulation technique. To check the efficiency of different clustering scheme against modeled constraints, we select four cluster based routing protocols; Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol (SEP), and Distributed Energy Efficient Clustering (DEEC). To validate our mathematical framework, we perform analytical simulations in MATLAB by choosing number of alive nodes, number of dead nodes, number of packets and number of CHs, as performance metrics.Comment: NGWMN with 7th IEEE International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201

Joint Data Routing and Power Scheduling for Wireless Powered Communication Networks

In a wireless powered communication network (WPCN), an energy access point supplies the energy needs of the network nodes through radio frequency wave transmission, and the nodes store the received energy in their batteries for their future data transmission. In this paper, we propose an online stochastic policy that jointly controls energy transmission from the EAP to the nodes and data transfer among the nodes. For this purpose, we first introduce a novel perturbed Lyapunov function to address the limitations on the energy consumption of the nodes imposed by their batteries. Then, using Lyapunov optimization method, we propose a policy which is adaptive to any arbitrary channel statistics in the network. Finally, we provide theoretical analysis for the performance of the proposed policy and show that it stabilizes the network, and the average power consumption of the network under this policy is within a bounded gap of the minimum power level required for stabilizing the network

Migration energy aware reconfigurations of virtual network function instances in NFV architectures

Network function virtualization (NFV) is a new network architecture framework that implements network functions in software running on a pool of shared commodity servers. NFV can provide the infrastructure flexibility and agility needed to successfully compete in today's evolving communications landscape. Any service is represented by a service function chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFIs) that are software modules executed on virtual machines. This paper deals with the migration problem of the VNFIs needed in the low traffic periods to turn OFF servers and consequently to save energy consumption. Though the consolidation allows for energy saving, it has also negative effects as the quality of service degradation or the energy consumption needed for moving the memories associated to the VNFI to be migrated. We focus on cold migration in which virtual machines are redundant and suspended before performing migration. We propose a migration policy that determines when and where to migrate VNFI in response to changes to SFC request intensity. The objective is to minimize the total energy consumption given by the sum of the consolidation and migration energies. We formulate the energy aware VNFI migration problem and after proving that it is NP-hard, we propose a heuristic based on the Viterbi algorithm able to determine the migration policy with low computational complexity. The results obtained by the proposed heuristic show how the introduced policy allows for a reduction of the migration energy and consequently lower total energy consumption with respect to the traditional policies. The energy saving can be on the order of 40% with respect to a policy in which migration is not performed