This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

Appearing in 1st IEEE International Workshop on Sensor Net Protocols and Applications (SNPA). Anchorage, Alaska, USA. May 11, 2003. RMST: Reliable Data Transport in Sensor Networks Fred Stann, John Heidemann Abstract – Reliable data transport in wireless sensor networks is a multifaceted problem influenced by the physical, MAC, network, and transport layers. Because sensor networks are subject to strict resource constraints and are deployed by single organizations, they encourage revisiting traditional layering and are less bound by standardized placement of services such as reliability. This paper presents analysis and experiments resulting in specific recommendations for implementing reliable data transport in sensor nets. To explore reliability at the transport layer, we present RMST (Reliable Multi- Segment Transport), a new transport layer for Directed Diffusion. RMST provides guaranteed delivery and fragmentation/reassembly for applications that require them. RMST is a selective NACK-based protocol that can be configured for in-network caching and repair. Second, these energy constraints, plus relatively low wireless bandwidths, make in-network processing both feasible and desirable [3]. Third, because nodes in sensor networks are usually collaborating towards a common task, rather than representing independent users, optimization of the shared network focuses on throughput rather than fairness. Finally, because sensor networks are often deployed by a single organization with inexpensive hardware, there is less need for interoperability with existing standards. For all of these reasons, sensor networks provide an environment that encourages rethinking the structure of traditional communications protocols. The main contribution is an evaluation of the placement of reliability for data transport at different levels of the protocol stack. We consider implementing reliability in the MAC, transport layer, application, and combinations of these. We conclude that reliability is important at the MAC layer and the transport layer. MAC-level reliability is important not just to provide hop-by-hop error recovery for the transport layer, but also because it is needed for route discovery and maintenance. (This conclusion differs from previous studies in reliability for sensor nets that did not simulate routing. [4]) Second, we have developed RMST (Reliable Multi-Segment Transport), a new transport layer, in order to understand the role of in- network processing for reliable data transfer. RMST benefits from diffusion routing, adding minimal additional control traffic. RMST guarantees delivery, even when multiple hops exhibit very high error rates. 1 Introduction Wireless sensor networks provide an economical, fully distributed, sensing and computing solution for environments where conventional networks are impractical. This paper explores the design decisions related to providing reliable data transport in sensor nets. The reliable data transport problem in sensor nets is multi-faceted. The emphasis on energy conservation in sensor nets implies that poor paths should not be artificially bolstered via mechanisms such as MAC layer ARQ during route discovery and path selection [1]. Path maintenance, on the other hand, benefits from well- engineered recovery either at the MAC layer or the transport layer, or both. Recovery should not be costly however, since many applications in sensor nets are impervious to occasional packet loss, relying on the regular delivery of coarse-grained event descriptions. Other applications require loss detection and repair. These aspects of reliable data transport include the provision of guaranteed delivery and fragmentation/ reassembly of data entities larger than the network MTU. Sensor networks have different constraints than traditional wired nets. First, energy constraints are paramount in sensor networks since nodes can often not be recharged, so any wasted energy shortens their useful lifetime [2]. This work was supported by DARPA under grant DABT63-99-1-0011 as part of the SCAADS project, and was also made possible in part due to support from Intel Corporation and Xerox Corporation. Fred Stann and John Heidemann are with USC/Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA, USA E-mail: fstann@usc.edu, johnh@isi.edu. 2 Architectural Choices There are a number of key areas to consider when engineering reliability for sensor nets. Many current sensor networks exhibit high loss rates compared to wired networks (2% to 30% to immediate neighbors)[1,5,6]. While error detection and correction at the physical layer are important, approaches at the MAC layer and higher adapt well to the very wide range of loss rates seen in sensor networks and are the focus of this paper. MAC layer protocols can ameliorate PHY layer unreliability, and transport layers can guarantee delivery. An important question for this paper is the trade off between implementation of reliability at the MAC layer (i.e. hop to hop) vs. the Transport layer, which has traditionally been concerned with end-to-end reliability. Because sensor net applications are distributed, we also considered implementing reliability at the application layer. Our goal is to minimize the cost of repair in terms of transmission.

RMST: Reliable Data Transport in Sensor Networks

Wireless sensor networks are often battery-powered, and hence extending the network lifetime is one of the primary concerns in the ubiquitous deployment of wireless sensor networks. One approach to efficiently utilize the limited energy supplies of the sensors is to have the medium access control (MAC) protocol duty-cycle the sensors, periodically putting the sensors to sleep and waking them up to reduce idle listening, which is energy intensive. Among duty-cycled MAC protocols, some protocols are synchronized so that nodes wake up at the same time in each cycle, and other protocols are asynchronous, where nodes have arbitrary offsets to start their cycles. For protocol designers, it is important to understand which type of duty-cycled MAC protocol should be chosen (synchronized or asynchronous), as well as what values should be assigned to the protocol parameters under a given network scenario in order to achieve a desirable performance for throughput, delay, or energy consumption. However, previous work to analyze the performance of different duty-cycled MAC protocols is either protocol-specific, or limited to one aspect of the performance metric. In this paper, we propose a Markov queuing model to analyze the throughput, delay, and energy consumption of both synchronized and asynchronous duty-cycled MAC protocols with applications to S-MAC and X-MAC. Our contributions include: 1) proposing a Markov queuing model to describe the queuing behavior of both synchronous and asynchronous duty-cycled nodes, 2) modeling the queue dynamics and the stationary probability of packet transmissions for S-MAC, a synchronized duty-cycled MAC protocol, to analyze its performance, 3) modeling the queue dynamics and the stationary probability of packet transmissions for X-MAC, an asynchronous duty-cycled MAC protocol, to analyze its performance, 4) providing comprehensive performance estimation and comparison for different duty-cycled MAC protocols, and 5) providing flexibility to tradeoff different performance metrics by optimizing the protocol parameters. Our model results are validated by comparing with NS-2 and Matlab simulations.

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Modeling and Performance Analysis for Duty-Cycled MAC Protocols with Applications to S-MAC and X-MAC

Unpredictable and heterogeneous links in a wireless sensor network require techniques to avoid low delivery rate and high delivery cost. Three commonly used techniques to help discover high quality paths include (1) link-layer retransmission, (2) blacklisting bad links, and (3) end-to-end routing metrics. Using simulation and testbed experiments, we present the rst systematic exploration of the tradeoffs of combinations of these approaches, quantifying the effects of each of these three techniques. We identify several key results: One is that per-hop retransmissions (ARQ) is a necessary addition to any other mechanism if reliable data delivery is a goal. Additional interactions between the services are more subtle. First, in a multihop network, either blacklisting or reliability metrics like ETX can provide consistent high-reliability paths when added to ARQ. Second, at higher deployment densities, blacklisting has a lower routing overhead than ETX. But at lower densities, blacklisting becomes less stable as the network partitions. These results are consistent across both simulation and testbed experiments. We conclude that ETX with retransmissions is the best choice in general, but that blacklisting may be worth considering at higher densities, either with or without ETX.

Interaction of Retransmission, Blacklisting, and Routing Metrics for Reliability in Sensor Network Routing

Data sensing and retrieval in wireless sensor systems have a widespread application in areas such as security and surveillance monitoring, and command and control in battlefields. In query-based wireless sensor systems, a user would issue a query and expect a response to be returned within the deadline. While the use of fault tolerance mechanisms through redundancy improves query reliability in the presence of unreliable wireless communication and sensor faults, it could cause the energy of the system to be quickly depleted. Therefore, there is an inherent trade-off between query reliability versus energy consumption in query-based wireless sensor systems. In this paper, we develop adaptive fault-tolerant quality of service (QoS) control algorithms based on hop-by-hop data delivery utilizing “source” and “path” redundancy, with the goal to satisfy application QoS requirements while prolonging the lifetime of the sensor system. We develop a mathematical model for the lifetime of the sensor system as a function of system parameters including the “source” and “path” redundancy levels utilized. We discover that there exists optimal “source” and “path” redundancy under which the lifetime of the system is maximized while satisfying application QoS requirements. Numerical data are presented and validated through extensive simulation, with physical interpretations given, to demonstrate the feasibility of our algorithm design.

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Adaptive Fault-Tolerant QoS Control Algorithms for Maximizing System Lifetime of Query-Based Wireless Sensor Networks

Sensor networks consist of very large number of resource constrained nodes, and to properly evaluate the performance of these networks a scalable ad-hoc wireless network simulator is needed. The JiST/SWANS is a highly scalable wireless network simulator with reported results for a million node network. However, it lacks an energy model. This work presents the design and implementation of an energy model for the JiST/SWANS simulator, which enables it to account for the energy consumed by wireless ad hoc and sensor networks' protocols. The instrumented energy model is validated through simulation. Results using JiST/SWANS and ns-2 are obtained and compared for similar network scenarios.

Implementation of an Energy Model for JiST/SWANS Wireless Network 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.

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

Wireless sensors are promising and revolutionary technology. The sensor devices are typically deployed in large number to form a communication network for monitoring the physical environment. These devices are battery powered and the lifetime of the device is dependent on the battery's life. Once the battery's energy is depleted, the node is considered dead and is no longer part of the network. Recharging the sensors' batteries is not feasible, and in some cases, is completely impossible. Due to their severe energy constraints and redundancy in sensed data, hierarchal architectures are usually suggested for these networks. These architectures have proven effective in extending the network life several folds. The LEACH network routing protocol is the first protocol to use clustering for energy conservation in Wireless Sensor Networks. LEACH designers observe that there is an ideal percentage of nodes that need to be cluster heads to achieve optimal energy performance. For their work and performance analysis they selected 5% as the number of cluster heads in the netwok. The majority of routing protocols for WSNs follow LEACH and use clustering for energy performance optimization. Most of these protocols have taken the 5% percentage of cluster head as their ideal working setting, without independently qualifying this assumption. In this work, we use simulation modeling to investigate the dependency of this cluster head percentage on the network node density. Our results show that this percentage is not universal for all network settings, and is indeed dependent on the density. These findings will add to the challenging task of WSNs hierarchical networking protocols design.

Investigation of the effects of network density on the optimal number of clusters in hierarchical Wireless Sensor Networks (WSNs)

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.

Analytical model of energy consumption in hierarchical 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.

Ahmed Badi

Papers

Implementation of an Energy Model for JiST/SWANS Wireless Network Simulator

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

Investigation of the effects of network density on the optimal number of clusters in hierarchical Wireless Sensor Networks (WSNs)

Analytical model of energy consumption in hierarchical wireless sensor networks

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