Energy efficient routing with delay guarantee for sensor networks

The paper presents a routing algorithm that maximizes the lifetime of a sensor network in which all data packets are destined to a single collection node. Lifetime is maximized by adjusting the number of packets traversing each node. The adjustment is carried out by transmitting over alternative routes. First part of the paper assumes that the worst case delay resulting from energy efficient routing is less than the maximum tolerable value. Ignoring the delay constraint of the network, the routes are selected as the solution to a linear programming (LP) problem in which the objective is to maximize the minimum lifetime of each node. The solution is first implemented in a centralized algorithm. The LP solution is then approximated by an iterative algorithm based on least cost path routing, in which each step is implemented efficiently in a distributed manner. Second part of the paper incorporates delay guarantee into energy efficient routing by limiting the length of the routing paths from each sensor node to the collection node. Simulations reveal that the lifetime of the network increases significantly by optimal routing and there is not always a tradeoff between the delay guarantee and the battery lifetime of the sensor network. The delay of the network keeps increasing as the maximum allowed delay value increases although the optimal lifetime and the connectivity of all the nodes to the collection node is achieved so including delay constraint in energy efficient routing improves the network performance

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network