Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.

Abstract — We experimentally investigate the impact of variable transmission power on link quality, and propose variable power link quality control techniques to enhance the performance of data delivery in wireless sensor networks. This study extends the state of the art in two key respects: first, while there are a number of previous results on power control techniques for wireless ad hoc and sensor networks, to our knowledge nearly all of them have been simulation or analytical studies that assume idealized link conditions; second, while there are several recent experimental studies that have shown the prevalence of non-ideal unreliable communication links in sensor networks, these have not thoroughly investigated the impact of variable transmission power. We perform a systematic set of experiments to analyze how transmission power changes affect the quality of low power RF wireless links between nodes. These experiments show how significant variation in link qualities occur in real-world deployments and how these effects strongly influence the effectiveness of transmission power control. We then present a packet-based transmission power control mechanism that incorporates blacklisting to enhance link reliability while minimizing interference. The effectiveness of the proposed scheme is demonstrated via testbed experiments.

Abstract — Many wireless sensor network applications must resolve the inherent conflict between energy efficient communication and the need to achieve desired quality of service such as end-to-end communication delay. To address this challenge, we propose the Real-time Power-Aware Routing (RPAR) protocol, which achieves application-specified communication delays at low energy cost by dynamically adapting transmission power and routing decisions. RPAR features a power-aware forwarding policy and an efficient neighborhood manager that are optimized for resource-constrained wireless sensors. Moreover, RPAR addresses important practical issues in wireless sensor networks, including lossy links, scalability, and severe memory and bandwidth constraints. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadlines missed and energy consumption compared to existing real-time and energy-efficient routing protocols. I.

Abstract — In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. However, determining which of the sensor nodes should be put into the sleep state is non-trivial. As the goal of allowing nodes to sleep is to extend network lifetime, we propose and analyze a Balanced-energy Scheduling (BS) scheme in the context of cluster-based sensor networks. The BS scheme aims to evenly distribute the energy load of the sensing and communication tasks among all the nodes in the cluster, thereby extending the time until the cluster can no longer provide adequate sensing coverage. Two related sleep scheduling schemes, the Distance-based Scheduling (DS) scheme and the Randomized Scheduling (RS) scheme are also studied in terms of the coefficient of variation of their energy consumption. Analytical and simulation results are presented to evaluate the proposed BS scheme. It is shown that the BS scheme extends the cluster’s overall network lifetime significantly while maintaining a similar sensing coverage compared with the DS and the RS schemes for sensor clusters. I.

Asymmetric transmission ranges caused due to transmit power control have the undesirable effect of increasing the number of hidden terminals in the network as well as increasing the unfairness in channel access. In this paper we present a new reactive power controlled MAC protocol, SHUSH, which tackles the above problems. We compare the performance of SHUSH with four other transmit power controlled MAC protocols and demonstrate that SHUSH achieves superior aggregate goodput, spatial reuse, fairness, and minimal energy consumption.

Wireless Mesh Networks (WMNs) are an emerging architecture based on multi-hop transmission. ISPs considers WMNs as a potential future technology to offer broadband Internet access. Therefore, in WMNs, the throughput capacity of the wireless backbone becomes a key factor, limiting the scalability in terms of users able to effectively take advantage of the network. Increasing the effective throughput capacity will support WMNs become a very cost-effective solution for wireless ISPs. Based on the analysis of the theoretical capacity bound derived by Gupta et al., we propose MRS (Mesh Routing Strategy), a novel cross layer routing solution. MRS is specifically designed for Wireless Mesh Networks, where routing is challenging due to the unreliable wireless medium. Traditional routing paradigms are not able to overcome this issue, resulting in an average throughput experienced by the network far lower than the theoretical throughput capacity bound. This paper shows how a cross-layer approach will consistently improve the throughput experienced by largescale multi-hop networks. We show through simulation that our proposal increases throughput while reducing the average transmitted power. Furthermore, MRS limits interference and gets closer to the theoretical throughput capacity bound.

The use of wireless mobile ad-hoc networks (MANETs) has gained rapid momentum, both in the commercial and non-commercial sectors. In the commercial sector, sensor networks are being considered for deployment for a wide variety of purposes including to sense robustness of elevators, bridges, and other structures and to explore the earth (e.g., oil, soil type, etc.). Examples in the noncommercial (military) sector include the use of MANETs in the battlefield. Regardless of the particular sector in which MANETs are being employed, one thing is common: MANETs are being used to collect, process, and relay vital information. As a result, it is critical that nodes in these networks be equipped to make decisions to ensure the integrity of information in an inherently unreliable environment. In this paper, we propose a Cross-layer Approach To Self-healing (CATS), in which nodes use information from each layer of the protocol stack to help the routing protocol maintain network reliability in the presence of failures. These actions serve both to provide uninterrupted communications amidst unforeseen failures and also to reduce packet latency and energy consumption. 1.

Energy efficiency and network capacity are two of the most important issues in wireless sensor networks. Topology-control algorithms have been proposed to maintain network connectivity while reducing energy consumption and improving network capacity. Several studies have also been performed to investigate critical conditions on several network parameters in order to ensure network k-connectivity (in the asymptotic sense). In this chapter, several problems (and their corresponding solutions) related to topology construction, maintenance, and connectivity in wireless sensor networks are discussed. Specifically, topics discussed include (1) various communication models and generation of random network topologies; (2) neighbor discovery and maintenance; (3) basic connectivity properties of wireless sensor networks (with the random unit graph model as the underlying model); (4) localized topology construction algorithms, along with their associated geometric structures in both homogeneous and heterogeneous networks; and (5) how to enhance fault tolerance in topology construction and connectivity. 10.1

Capacity is an important property for QoS support in Mobile Ad Hoc Networks (MANETs) and has been extensively studied. However, most approaches rely on simplified models (isotropic radio propagation, unidirectional links, perfect scheduling, perfect routing, etc.) and either provide asymptotic bounds or are based on integer linear programming solvers. In this paper we present a probabilistic approach to capacity calculation by linking the normalized throughput of a communication pair in an ad hoc network to the connection probability of the two nodes in a so called schedule graph GT(N, E). The effective throughput of a random network is modelled as a random variable and expected values of it are computed using Monte-Carlo methods. A schedule graph GT(N, E) for a given network directly emerges from the physical properties of the network, like node distribution, radio propagation or channel assignment. The modularity of the approach allows for capacity analysis under more realistic network models. In the paper throughput capacity is computed for various forms of network configurations and the results are compared to simulation results obtained with ns-2.

The capacity of wireless multi-hop networks has been studied extensively in recent years. Most existing work tackles the problem from an asymptotic perspective and assumes a simplified physical layer model, as e.g., the protocol interference model or the path loss radio propagation. Real life network planning, provisioning and deployment can only be done with more precise statements about capacity in finite networks. With this in mind, we adopt a numerical approach based on Monte-Carlo methods to study capacity under various interference and radio propagation models, including the physical interference model and log-normal shadowing radio propagation. Our results indicate that, depending on the interference model, capacity may experience a three phase transition related to the connectivity of the network. We further show that throughput capacity increases in the presence of randomized radio propagation, even above the critical node density. Our analysis of the numerical data illustrates that log-normal shadowing creates more interference, but decreases the total amount of transmissions to be scheduled.