Dynamic master selection in wireless networks

Abstract. Mobile wireless networks need to maximize their network lifetime (defined as the time until the first node runs out of energy). In the broadcast network lifetime problem, all nodes are sending broadcast traffic, and one asks for an assignment of transmit powers to nodes, and for sets of relay nodes so that the network lifetime is maximized. The selection of a dynamic relay set consisting of a single node (the ‘master’), can be regarded as a special case, providing lower bounds to the optimal lifetime in the general setting. This paper provides a first analysis of a ‘dynamic master selection’ algorithm

Directed triangles in directed graphs

AbstractWe show that each directed graph (with no parallel arcs) on n vertices, each with indegree and outdegree at least n/t where t=2.888997… contains a directed circuit of length at most 3

Energy efficient networking via dynamic relay node selection in wireless networks

Mobile wireless ad-hoc networks need to maximize their network lifetime (defined as the time until the first node runs out of energy). In the broadcast network lifetime problem, all nodes are sending broadcast traffic, and one asks for an assignment of transmit powers to nodes, and for sets of relay nodes so that the network lifetime is maximized. The selection of a dynamic relay set consisting of a single node (the `master'), can be regarded as a special case, providing lower bounds to the optimal lifetime in the general setting. This paper provides a preliminary analysis of such a `dynamic master selection' algorithm, comparing relaying to direct routing

An analysis of the lifetime of OLSR networks

The Optimized Link State Routing (OLSR) protocol is a well-known route discovery protocol for ad-hoc networks. OLSR optimizes the flooding of link state information through the network using multipoint relays (MPRs). Only nodes selected as MPRs are responsible for forwarding control traffic. Many research papers aim to optimize the selection of MPRs with a specific purpose in mind: e.g., to minimize their number, to keep paths with high Quality of Service or to maximize the network lifetime (the time until the first node runs out of energy). In such analyzes often the effects of the network structure on the MPR selection are not taken into account. In this paper we show that the structure of the network can have a large impact on the MPR selection. In highly regular structures (such as grids) there is even no variation in the MPR sets that result from various MPR selection mechanisms. Furthermore, we study the influence of the network structure on the network lifetime problem in a setting where at regular intervals messages are broadcasted using MPRs. We introduce the ’maximum forcedness ratio’, as a key parameter of the network to describe how much variation there is in the lifetime results of various MPR selection heuristics. Although we focus our attention to OLSR, being a widely implemented protocol, on a more abstract level our results describe the structure of connected sets dominating the 2-hop neighborhood of a node

Increasing network lifetime by battery-aware master selection in radio networks

Mobile wireless communication systems often need to maximize their network lifetime (defined as the time until the first node runs out of energy). In the broadcast network lifetime problem, all nodes are sending broadcast traffic, and one asks for an assignment of transmit powers to nodes, and for sets of relay nodes so that the network lifetime is maximized. The selection of a relay set consisting of a single node (the ‘master’), can be regarded as a special case of this problem. We provide a mean value analysis of algorithms controlling the selection of a master node with the objective of maximizing the network lifetime. The results show that already for small networks simple algorithms can extend the average network lifetime considerably

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

A first Experimental Investigation of the Practical Efficiency of Battery Scheduling

Nowadays, mobile devices are used more and more, and their battery lifetime is a key concern. In this paper, we concentrate on a method called battery scheduling with the aim to optimize the battery lifetime of mobile devices. This technique has already been largely theoretically studied in other papers. It consists, for systems containing multiple batteries, in switching the load from one battery to the other. Then, while following a given scheduling sequence, advantage can be taken from the recovery and rate capacity effects. However, little studies with experimental data of battery scheduling have been found. In this paper we describe a simple setup for measuring the possible gain of battery scheduling, and give some exploratory results for two types of real batteries: a smart Li-Ion battery used in the Thales personal communication system and a more commonly used NiCd battery. The results, so far, show that system lifetime extension is not systematic, and generally can only reach less then 10%

An optimal query assignment for wireless sensor networks

With the increased use of large-scale real-time embedded sensor networks, new control mechanisms are needed to avoid congestion and meet required Quality of Service (QoS) levels. In this paper, we propose a Markov Decision Problem (MDP) to prescribe an optimal query assignment strategy that achieves a trade-off between two QoS requirements: query response time and data validity. Query response time is the time that queries spend in the sensor network until they are solved. Data validity (freshness) indicates the time elapsed between data acquisition and query response and whether that time period exceeds a predefined tolerance. We assess the performance of the proposed model by means of a discrete event simulation. Compared with three other heuristics, derived from practical assignment strategies, the proposed policy performs better in terms of average assignment costs. Also in the case of real query traffic simulations, results show that the proposed policy achieves cost gains compared with the other heuristics considered. The results provide useful insight into deriving simple assignment strategies that can be easily used in practice