Ahmed Badi

Implementation of the Sensor-MAC Protocol for the JiST/SWANS Simulator

Wireless sensor networks consist of very large number of resource constrained nodes. Therefore, protocols and applications for wireless sensor networks need to be very scalable and efficient. To properly evaluate the performance of these networks a scalable ad-hoc wireless network simulator is needed. The JIST/SWANS is a highly scalable ad hoc wireless network simulator that has been recently developed. However, JIST/SWANS does not have an energy model or a MAC protocol for wireless sensor networks. In recent work, we developed an energy model for JiST/SWANS. This work presents our implementation of the S-MAC protocol for the JiST/SWANS simulator. The implementation is validated through simulations. Results using JiST/SWANS and NS-2 are obtained and compared for similar network scenarios.

Analytical model of energy consumption in hierarchical wireless sensor networks

Here we propose an analytical model of energy usage hierarchical wireless sensor network protocols such as LEACH [1]. LEACH has been used as a foundation for much of the wireless sensor network research, so results addressing the underlying nature of these systems build understanding of a wide range of existing protocols. First, we derive the probability density functions of the distance to the nearest cluster head, the distance to the nearest cluster head squared, and the expected number of nodes per cluster. These results are then applied to produce a model of the amount of average energy used per node for each data report. Using this model we give an analytic expression for the optimal cluster-head selection rate. The model is further improved to give an approximate adjustment for distortions in energy usage near the edges of the field. This final model is then compared to the simulation results presented in the original LEACH paper [1] and shown to be accurate. Sensor network protocol researchers can apply results presented here to improve performance of existing systems by making the cluster head selection rate adaptive to external factors.

A Functional Component Based Framework for Cross-Layer Design

We present a framework for cross-layer optimization in small, resource-constrained systems which require a high degree of optimization. We argue that often these systems allow for a departure from conventional network stack design principles opening up broad opportunities for optimizations. We examine these new opportunities and propose a design strategy to take advantage of them. Simulation results are presented in support of our design framework proposal and as motivation for future work in this important area.

Impact of transmission-related parameters on the energy performance of cluster-based routing protocols for wireless sensor networks

We investigate the effectiveness of cluster-based routing protocols in extending the lifetime for energy-constrained wireless sensor networks. Most routing protocol designs for wireless sensors exploit the fact that they are not communication networks in the classical meaning. They can rather be considered as distributed systems where all the different entities collaborate to perform a given task or set of tasks. This fact is used to trade per node fairness and other networking qualities for designs that are energy efficient. The networking layer is responsible for the end to end routing and delivery of data messages. Routing decisions affect the number of transmissions, the distance covered per transmission and the load placed on the intermediate nodes that participate in relaying the messages. This makes the design of energy efficient protocols in the routing layer very critical for extending the network lifetime. For these reasons, the network layer has attracted more attention than the other layers for energy-efficient designs. This study focuses on common parameters of well-known cluster based routing protocols.We use LEACH protocol as a representative to investigate their energy performance sensitivity to the number of clusters, the location of the base station and the data message size.

Using individualized link power settings for energy optimization in hierarchical wireless sensor networks (WSNs)

Wireless sensors are new revolutionary technology. The sensor devices are typically deployed in large numbers to form a communication network. Due to their severe energy constraints and redundancy in sensed data, hierarchal architectures are usually suggested for these networks. In this work, we propose further energy savings by optimizing the local transmission power between the node and its cluster head. The local node to cluster head transmission power is set to the minimum level that guarantees network connectivity. Often, due to close proximity of the cluster head or superior link connectivity, this local transmission power setting is still too high. We present an algorithm that optimizes the local transmission power while ensuring reliable data delivery. The performance of the protocol is evaluated using simulation. Results show significant energy savings while satisfying reliability constraint.

MAC Layer Dynamic Backoff Scheme for Message Delivery Reliability in Wireless Sensor Networks

We propose using dynamic backoff on CSMA-type MAC layer protocols to improve message delivery reliability in wireless sensor networks. It is assumed that the MAC layer is able to determine message reliability requirements by reading a reliability data bit embedded within the message. The basic concept is to apply shorter random backoff times to important messages. This gives them the opportunity to test the availability of the communication channel more frequently, enhancing their chance of finding the medium idle. However, this technique might produce the opposite result by allowing the MAC layer to retry sending the important messages in a higher frequency. As a result important messages may reach their maximum retry limit, and get removed from the network. To counteract, we also propose giving the messages a maximum retry limit based on their type. In this setting, important messages will have a higher maximum retry limit. We developed a simulation program to validate our proposed dynamic backoff scheme. The results obtained show that under reasonable network utilization level, the latency is reduced for important messages. Under heavy network utilization conditions, the dynamic backoff scheme drops normal messages leaving the network resources available to handle the delivery of important messages.

The next challenge for wireless sensor networks: Addressing practical issues

Academic research in wireless sensor networks (WSNs) has been active for more than a decade. Many algorithms and solutions have been proposed to address several of the challenges this field present. Nevertheless, this technology has not seen the commercialization and the industrial adoption that match the fields research maturity. In this paper, we identify and discuss a new set of practical challenges that are not usually considered in academic research. Addressing these challenges is critical to improving industrial awareness and engagement. The WSNs technology cannot reach its full potential until and unless these challenges have been understood, addressed and resolved.

Cross-layer design for wireless networks with cognitive controllers

A new approach to wireless network design featuring a cognitive controller stack component is presented. The controller uses system status information from the protocol components to tune the behavior of the network stack to achieve a given performance objective. A controller design strategy using a machine learning algorithm and a simulator is proposed, implemented, and tested. Results with ad-hoc wireless networks show the architecture and design strategy are capable of producing a network stack that outperforms the existing protocol stack for given performance objectives. The techniques presented give network designers the flexibility to easily tune the performance of their networks to suit their application.

Dynamic entity distribution in parallel discrete event simulation

Event based simulations are an important scientific application in many fields. With the rise of cluster computing, distributed event simulation optimization becomes an essential research topic. This paper identifies cross-node event queues as a major source of slow down in practical parallel event simulations and proposes dynamically moving entities between nodes to minimize such remote event queues. The problem statement is formalized and an algorithm based on an approximation algorithm for the Capacitated Minimum K-Cut Problem is proposed. The algorithm is simulated and results are presented that show its effectiveness. For simulations with reasonably regular structural relationships between entities, reductions of remote entity queues from 80 to 90 % are demonstrated.

Emerging Concepts in Collective Sensing

A new computing paradigm where computing platforms are aware of their physical surroundings is emerging and will be commonplace in the near future. Millimeter-scale miniature devices with sensing, processing, and wireless communication capabilities will change the way we live. These systems will provide the technology behind numerous collective sensing applications expected in the near future. Collective sensing is the collaboration between multiple networked sensor devices in sharing their readings. Through collective sensing, sensor network applications are able to provide coverage, reliability, target tracking, and continuous monitoring. Furthermore, using heterogeneous sensors, collective sensing applications can provide accurate and comprehensive view of the environment or the monitored phenomenon. This results in network intelligence that far exceeds the capabilities of any individual sensor device. This chapter covers current and emerging concepts and applications in collective sensing and discusses their future directions.