Aylin Aksu

Reliable Multi-hop Routing with Cooperative Transmissions in Energy-Constrained Networks

We present a novel approach in characterizing the optimal reliable multi-hop virtual multiple-input single-output (vMISO) routing in ad hoc networks. Under a high node density regime, we determine the optimal cardinality of the cooperation sets at each hop on a path minimizing the total energy cost per transmitted bit. Optimal cooperating set cardinality curves are derived, and they can be used to determine the optimal routing strategy based on the required reliability, transmission power, and path loss coefficient. We design a new greedy geographical routing algorithm suitable for vMISO transmissions, and demonstrate the applicability of our results for more general networks.

An Energy-Efficient Routing Protocol for Networks with Cooperative Transmissions

The cooperative transmissions emulate multi-antenna systems, and can be used to reduce the total energy consumption. In this paper, our objective is to quantify the advantages of using cooperative transmissions in extending the network lifetime of the energy-constrained wireless networks. We develop a detailed energy consumption model suitable for systems with cooperative transmissions taking into account the effects of channel fading. We then design a new cooperating node set selection and routing algorithm. The algorithm greedily chooses the cooperating nodes and the paths that has the minimum cost. We use a new cost metric which takes into account the transmission and reception energy costs, residual node energies, the rate of the space time block codes used, and the diversity gain provided by the cooperative transmissions. Our simulation results indicate that the network lifetime with cooperative transmissions is on the average 50% more than the lifetime with traditional transmissions. We also show that cooperative transmissions provide the maximum benefit in medium density networks and the lifetime increases when the network gets more clustered.

On Security and Reliability Using Cooperative Transmissions in Sensor Networks

Cooperative transmissions have received recent attention and research papers have demonstrated their benefits for wireless networks. Such benefits include improving the reliability of links through diversity and/or increasing the reach of a link compared to a single transmitter transmitting to a single receiver (single-input single-output or SISO). In one form of cooperative transmissions, multiple nodes can act as virtual antenna elements and provide diversity gain or range improvement using space-time coding. In a multi-hop ad hoc or sensor network, a source node can make use of its neighbors as relays with itself to reach an intermediate node with greater reliability or at a larger distance than otherwise possible. The intermediate node will use its neighbors in a similar manner and this process continues till the destination is reached. Thus, for the same reliability of a link as SISO, the number of hops between a source and destination may be reduced using cooperative transmissions as each hop spans a larger distance. However, the presence of malicious or compromised nodes in the network impacts the benefits obtained with cooperative transmissions. Using more relays can increase the reach of a link, but if one or more relays are malicious, the transmission may fail. However, the relationships between the number of relays, the number of hops, and success probabilities are not trivial to determine. In this paper, we analyze this problem to understand the conditions under which cooperative transmissions fare better or worse than SISO transmissions. We take into consideration additional parameters such as the path-loss exponent and provide a framework that allows us to evaluate the conditions when cooperative transmissions are better than SISO transmissions. This analysis provides insights that can be employed before resorting to simulations or experimentation.

Reduction of location estimation error using neural networks

The objective of this work is to estimate the locations of Bluetooth enabled devices. Collecting received signal strength from a device may help with estimating its location. However, for indoor environments, the signal attenuation model becomes complex and difficult to represent concisely due to multi-path and small-scale fading effects. The flexible modeling and learning capabilities of neural networks provide lower errors in determining the position even in the presence of these destructive effects. A standard backpropagation learning algorithm was employed to minimize the error between target and estimated locations in order to find the weights of the links of the neural network. Simulation results show that a neural network with three input units and 8 hidden layer units and two output units can provide 75cm root mean square (RMS) error.

Multi-hop cooperative transmissions in wireless sensor networks

We present the optimal number of cooperating nodes in multi-hop virtual multiple-input single-output (vMISO) based cooperative wireless sensor networks as a result of an energy consumption optimization problem in a limiting case of very dense networks. The main advantage of vMISO considered in this work is the increase in transmission range due to diversity and power gain. We demonstrate that it is best to have two cooperating nodes, when vMISO is allowed to have multiple transmissions without power control.

Joint sensor selection and data routing in sensor networks

We propose a new joint sensor selection and routing algorithm, which selects a set of sensor nodes (sensing nodes) in a sensor network to take measurements, and determines a set of paths connecting the sensing nodes to the sink node. Our objective is to maximize the network lifetime, while satisfying the data precision required by the user. We first develop a multi-objective optimization model for this problem and design the near-optimal OPT-RE algorithm based on this model for network lifetime maximization. Next, we design a low complexity heuristic called SP-RE. SP-RE first labels the links between the nodes with a metric which trades off the residual energies of the transmitting and receiving nodes with the required transmission and reception energy. Then, SP-RE calculates the shortest paths from all nodes to the sink, and identifies the node which is closest to the sink as a sensing node. This process is repeated until the required data precision is satisfied. We demonstrate by simulations that SP-RE and OPT-RE can increase the network lifetime several orders of magnitude compared to naive approaches.

A practical routing and MAC framework for maximum lifetime sensor telemetry

The recent progress in sensor and wireless communication technologies has enabled the design and implementation of new applications such as sensor telemetry which is the use of wireless sensors to gather more fine-grained information from products, people and places. In this work, we consider a realistic telemetry application in which a large 2-dimensional area is periodically monitored by a sensor network which gathers data from equally spaced sample points. The objective is to maximize the lifetime of the network by jointly selecting the sensing nodes, the node transmission powers and the route to the base station from each sensing node. We develop an optimization-based algorithm OPT-RE, and a low complexity algorithm SP-RE for this purpose, and analyze their dynamics through extensive numerical studies. Our results indicate that SP-RE is a promising algorithm which has comparable performance to that of the more computationally intensive OPT-RE algorithm. The energy consumption is significantly affected by the channel access method, and in this paper, we also compare the effects of the collision-free TDMA, and contention-based CSMA/CA methods.

Energy efficient and reliable routing with cooperative diversity in wireless Ad-Hoc networks

The problem of maximizing network lifetime in wireless ad-hoc networks is addressed with a cooperative routing approach. The network lifetime optimization problem is defined as a linear programming problem and it is shown with simulations that networks utilizing cooperative transmission have larger lifetime than the networks not utilizing.