Power-aware base station positioning for sensor networks

Abstract

Abstract-We consider the problem of positioning data collecting base stations in a sensor network. We show that in general, the choice of positions has a marked influence on the data rate, or equivalently, the power efficiency, of the network. In our model, which is partly motivated by an experimental environmental monitoring system, the optimum data rate for a fixed layout of base stations can be found by a maximum flow algorithm. Finding the optimum layout of base stations, however, turns out to be an NP-complete problem, even in the special case of homogeneous networks. Our analysis of the optimum layout for the special case of the regular grid shows that all layouts that meet certain constraints are equally good. We also consider two classes of random graphs, chosen to model networks that might be realistically encountered, and empirically evaluate the performance of several base station positioning algorithms on instances of these classes. In comparison to manually choosing positions along the periphery of the network or randomly choosing them within the network, the algorithms tested find positions which significantly improve the data rate and power efficiency of the network.

Optimal Placement of Multiple Interconnected Gateways in Heterogeneous Wireless Sensor Networks

“…In [10] heuristic algorithms based on local search and greedy techniques are proposed. Their objective is finding the best sensor nodes to be selected as gateways.…”

“…Indeed, as the network grows, the amount of information that must be delivered to the sink by surrounding nodes increases creating traffic and energy consumption bottlenecks. A promising alternative approach is based on the use of additional concentration nodes, gateways, that allow to spread the load and also to keep multi-hop paths within a reasonable length [8,9,10]. Also in this case gateway positioning is a key element for designing efficient networks.…”

“…Generally speaking, gateways are more powerful and expensive devices with respect to sensors and a reasonable objective is minimizing their number while matching constraints on energy efficiency and network quality [8,10,12]. However, this approach focuses on the WSN only neglecting the problem of interconnecting the gateways to the sink or more in general to the network where application servers are located.…”

An online energy-efficient routing protocol with traffic load prospects in wireless sensor networks

“…Some researchers formulate the energy-efficient problem to max-flow problems (Zussman and Segall, 2003;Bogdanov et al, 2004;Sadagopan and Krishnamachari, 2004), and (Chang and Tassiulas, 2000;Chang and Tassiulas, 2004) propose a class of Flow Augmentation (FA) algorithms and a flow redirection algorithm. In addition, protocols are designed to accomplish energy efficiency from data fusion (Heinzelman et al, 2000;Luo et al, 2005a;Ciancio et al, 2006).…”

“…Among them, energy-efficient routing is one of the most important issues. Existing research can be categorised into classes such as: (1) least cost path-based approaches (Li et al, 2001;Toh, 2001;Hong et al, 2002;Misra and Banerjee, 2002;Akkaya and Younis, 2003;Kar et al, 2003;Gao and Zhang, 2004;Park and Sahni, 2006), (2) max-flow problem-based approaches (Chang and Tassiulas, 2000;Zussman and Segall, 2003;Chang and Tassiulas, 2004;Sadagopan and Krishnamachari, 2004), (3) data fusion and network coding approach (Heinzelman et al, 2000;Luo et al, 2005a;Ciancio et al, 2006) and (4) topology and deployment control-based approaches (Shah and Rabaey, 2002;Bogdanov et al, 2004;Kannan et al, 2004;Chatterjee et al, 2005;Kawadia and Kumar, 2005), etc. In these researches, different design objectives and metrics are addressed.…”