Data MULEs: modeling a three-tier architecture for sparse sensor networks

Shah, Rahul; Roy, Sumit; Jain, Shailendra Pratap; Brunette, Waylon

doi:10.1109/snpa.2003.1203354

Cited by 970 publications

(704 citation statements)

References 12 publications

Supporting

Mentioning

698

Contrasting

Unclassified

Order By: Relevance

“…Davis et al [10] evaluate several algorithms for managing DTN routing when buffers are the limited resource in the network. Shah et al [22] propose to exploit mobile entities to transport data to conserve energy in resource-limited sensors. Proactive approaches dictate or restrict the movement of devices for routing.…”

Section: Related Workmentioning

confidence: 99%

Capacity Enhancement using Throwboxes in DTNs

Zhao

Yang

Ammar

et al. 2006

2006 IEEE International Conference on Mobile Ad Hoc and Sensor Systems

195

179

View full text Add to dashboard Cite

Abstract-Disruption Tolerant Networks (DTNs) are designed to overcome limitations in connectivity due to conditions such as mobility, poor infrastructure, and short range radios. DTNs rely on the inherent mobility in the network to deliver packets around frequent and extended network partitions using a store-carry-andforward paradigm. However, missed contact opportunities decrease throughput and increase delay in the network. We propose the use of throwboxes in mobile DTNs to create a greater number of contact opportunities, consequently improving the performance of the network. Throwboxes are wireless nodes that act as relays, creating additional contact opportunities in the DTN. We propose algorithms to deploy stationary throwboxes in the network that simultaneously consider routing as well as placement. We also present placement algorithms that use more limited knowledge about the network structure. We perform an extensive evaluation of our algorithms by varying both the underlying routing and mobility models. Our results suggest several findings to guide the design and operation of throwbox-augmented DTNs.

show abstract

Section: Related Workmentioning

confidence: 99%

Capacity Enhancement using Throwboxes in DTNs

Zhao

Yang

Ammar

et al. 2006

2006 IEEE International Conference on Mobile Ad Hoc and Sensor Systems

195

179

View full text Add to dashboard Cite

show abstract

“…Oftentimes, the sensors need not be mobile, but they may require a mobile device to collect their data and deliver it to a base station. These types of mobile entities are referred to as data mules [16]. It is generally assumed that data mules can recharge their power source automatically.…”

Section: Mwsn Architecturesmentioning

confidence: 99%

A Survey on Localization for Mobile Wireless Sensor Networks

Amundson

Koutsoukos

2009

Lecture Notes in Computer Science

255

142

View full text Add to dashboard Cite

Abstract. Over the past decade we have witnessed the evolution of wireless sensor networks, with advancements in hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been much focus on mobile sensor networks, and we have even seen the development of small-profile sensing devices that are able to control their own movement. Although it has been shown that mobility alleviates several issues relating to sensor network coverage and connectivity, many challenges remain. Among these, the need for position estimation is perhaps the most important. Not only is localization required to understand sensor data in a spatial context, but also for navigation, a key feature of mobile sensors. In this paper, we present a survey on localization methods for mobile wireless sensor networks. We provide taxonomies for mobile wireless sensors and localization, including common architectures, measurement techniques, and localization algorithms. We conclude with a description of real-world mobile sensor applications that require position estimation.

show abstract

“…The sensing data can be collected by mobile robots, such as the data mules proposed in Chakrabarti et al (2005) and Shah et al (2003) and thus no energy is consumed by the sensors for the transmission of the sensed data.…”

Section: Solutions For the Ar-sc Problemmentioning

confidence: 99%

Improving network lifetime using sensors with adjustable sensing ranges

Cardei¹,

Wu²,

Lu³

2006

IJSNET

111

View full text Add to dashboard Cite

This paper addresses the target coverage problem in wireless sensor networks with adjustable sensing range. Communication and sensing consume energy, therefore efficient power management can extend network lifetime. In this paper, we consider a large number of sensors with adjustable sensing range that are randomly deployed to monitor a number of targets. Since targets are redundantly covered by multiple sensors, to conserve energy resources, sensors can be organised in sets, activated successively. In this paper, we address the Adjustable Range Set Covers (AR-SC) problem that has as its objective finding a maximum number of set covers and the ranges associated with each sensor, such that each sensor set covers all the targets. A sensor can participate in multiple sensor sets, but the sum of the energy spent in each set is constrained by the initial energy resources. In this paper, we mathematically model solutions to this problem and design heuristics that efficiently compute the sets. Simulation results are presented to verify our approaches.

show abstract

Data MULEs: modeling a three-tier architecture for sparse sensor networks

Cited by 970 publications

References 12 publications

Capacity Enhancement using Throwboxes in DTNs

Capacity Enhancement using Throwboxes in DTNs

A Survey on Localization for Mobile Wireless Sensor Networks

Improving network lifetime using sensors with adjustable sensing ranges

Contact Info

Product

Resources

About