Nicholas Timmons

Analysis of the performance of IEEE 802.15.4 for medical sensor body area networking

For the first time, this paper presents an analysis of the performance of the IEEE 802.15.4 low power, low data rate wireless standard in relation to medical sensor body area networks. This is an emerging application of wireless sensor networking with particular performance constraints, including power consumption, physical size, robustness and security. In the analysis presented, the star network configuration of the 802.15.4 standard at 2.4 GHz was considered for a body area network consisting of a wearable or desk mounted coordinator outside of the body with up to 10 body implanted sensors. The main consideration in this work was the long-term power consumption of devices, since for practical reasons, implanted medical devices and sensors must function for at least 10 to 15 years without battery replacement. The results show that when properly configured, 802.15.4 can be used for medical sensor networking when configured in non-beacon mode with low data rate asymmetric traffic. Beacon mode may also be used, but with more severe restrictions on data rate and crystal tolerance.

Energy-Balanced Rate Assignment and Routing Protocol for Body Area Networks

In Body Area Networks (BANs), quality of service is needed to provide reliable data communication over prioritized data streams coming from energy constrained sensors attached to, or possibly implanted in, patients. In this work, we focus on BAN for real-time data streaming applications, where the real-time nature of data streams is of critical importance for providing a useful and efficient sensorial feedback for the user while system lifetime should be maximized. Thus, bandwidth, throughput and energy efficiency of the communication protocol must be carefully optimized. In this paper, we present an Energy-Balanced Rate Assignment and Routing Protocol (EBRAR). EBRAR selects routes based on the residual energy, thus, instead of continuously routing data through an optimized (energy efficient) fixed path, the data is transported more intelligently and the burden of forwarding the data is more equally spread among the nodes. Another unique property of EBRAR is its ability to provide adaptive resource allocation. Our experimental results show that the proposed protocol performs well in terms of balancing energy consumption across the BAN and thus guarantees longer network lifetime.

Cross-layer optimization protocol for guaranteed data streaming over Wireless Body Area Networks

In this paper, we study the problem of routing, bandwidth and flow assignment in Wireless Body Area Networks (BANs). Our solution considers BAN for real-time data streaming applications, where the real-time nature of data streams is of critical importance for providing a useful and efficient sensorial feedback for the user while system lifetime should be maximized. Thus, bandwidth and energy efficiency of the communication between energy constrained sensor nodes must be carefully optimized. The proposed solution takes into account nodes residual energy during the establishment of the routing paths and adaptively allocates bandwidth to the nodes in the network. We also formulate the joint routing tree construction and bandwidth allocation problem as an Integer Linear Program that maximizes the network utility while satisfying the QoS requirements. We compare the resulting performance of our protocol with the optimal solution, and show that it closes a considerable portion of the gap from the theoretical optimal solution.

Intelligent routing strategies in wireless sensor networks for smart cities applications

In the context of Smart City environments, wireless sensor networking is playing a major role when enabling the utilization of networked infrastructures to introduce or improve a wide variety of services to be available to the citizens. How nodes communicate with each other is a key issue in these types of networks. This work presents a simple but yet efficient network discovery and tree construction protocol as well as an intelligent metric for route selection in smart environments that combines several parameters through the use of fuzzy logic. We have carried out an extensive set of experiments using the I3ASensorBed testbed, that shows the efficiency of our proposal, when compared to other well known routing metrics by reducing the system load and increasing the network efficiency.

A cross-layer QoS-aware optimization protocol for guaranteed data streaming over wireless body area networks

In this paper, we study the problem of routing, bandwidth and flow assignment in wireless body area networks (BANs). We present an adaptive joint routing and bandwidth allocation protocol for traffic streaming in BAN. Our solution considers BAN for real-time data streaming applications, where the real-time nature of data streams is of critical importance for providing a useful and efficient sensorial feedback for the user while system lifetime should be maximized. Thus, bandwidth and energy efficiency of the communication between energy constrained sensor nodes must be carefully optimized. The proposed solution takes into account nodes’ residual energy during the establishment of the routing paths and adaptively allocates bandwidth to the nodes in the network. We also formulate the joint routing tree construction and bandwidth allocation problem as Mixed Integer Linear Program that maximizes the network utility while satisfying the QoS requirements. We compare the resulting performance of our protocol with the optimal solution, and show that it closes a considerable portion of the gap from the theoretical optimal solution.

Energy-Efficient Multicast tree construction protocol for real-time data streaming in WSNs

This paper revisits the problem of multisession multicast tree construction with bandwidth allocation in wireless sensor networks. Previous work has shown that when the goal is to find multicast routing tree, the problem becomes NP-complete. In this work, we present a heuristic Energy-Efficient Multisession Multicast protocol (EEMM) that uses fuzzy logic to evaluate nodes and network conditions during the multicast tree construction process. Our proposed solution includes an online rate assignment algorithm that aims at maximizing the overall network throughput by accepting as many streams in the network as possible. The proposed solution allows receivers to request multiple sessions from, possibly, different sources with different data rates. We conduct extensive evaluations to study the performance of the proposed protocol compared to other existing approaches, namely shortest path and minimum transmission tree routing. Simulation results show that our protocol effectively improves the network throughput and utilization, while conserving and balancing out per node energy consumption ensure prolonged network lifetime.

An adaptive bandwidth allocation scheme for data streaming over body area networks

We present an adaptive joint routing and bandwidth allocation scheme for traffic streaming in Body Area Networks (BAN). Our solution considers BAN for real-time data streaming applications, where the real-time nature of data streams is of critical importance for providing a useful and efficient sensorial feedback for the user while system lifetime should be maximized. Thus, bandwidth and energy efficiency of the communication protocol must be carefully optimized. The proposed solution takes into account nodes residual energy during the establishment of the routing paths and adaptively allocates bandwidth to the nodes in the network. We also formulate the bandwidth allocation problem as an Integer Linear Program that maximizes the network utility while satisfying the QoS requirements. We compare the resulting performance of our scheme with the optimal solution, and show that it closes a considerable portion of the gap from the theoretical optimal solution.

EBRAR: Energy-balanced rate allocation and routing protocol for body area networks

In this work, we focus on Body Area Networks (BANs) for real-time data streaming applications, where the realtime nature of data streams is of critical importance for providing a useful and efficient sensorial feedback for the user while system lifetime should be maximized. Thus, bandwidth, throughput and energy efficiency of the communication protocol must be carefully optimized. In this paper, we present an Energy-Balanced Rate Allocation and Routing Protocol (EBRAR). EBRAR selects routes based on the residual energy, thus, instead of continuously routing data through an optimized (energy efficient) fixed path, the data is transported more intelligently and the burden of forwarding the data is more equally spread among the nodes. Another unique property of EBRAR is its ability to provide adaptive resource allocation. Our experimental results show that the proposed protocol performs well in terms of energy balance, network lifetime and utility.

Intelligent multicast tree construction protocol with optimal bandwidth allocation for WSNs

This paper addresses the problem of multisession multicast tree construction with bandwidth and rate allocation in wireless sensor networks. Previous work has shown that when the goal is to find multicast routing tree, the problem becomes NP-complete. In this work, we present a heuristic Multisession Multicast Routing and Bandwidth Allocation protocol, termed MMBA, that makes use of fuzzy logic to evaluate nodes and network conditions during the multicast tree construction process. Rate assignment is optimized in order to be able to accept as many data streams (i.e., sessions) at the highest possible data rate in the sensor network as possible, allowing source nodes to transmit at maximum available rate, while maximizing the overall network throughput and utility. We conduct extensive evaluations to study the performance of the proposed protocol compared to existing approaches such as shortest path, Steiner and minimum transmission tree. Simulation results show that our protocol effectively improves the network throughput and utilization, while conserving per node energy consumption.