Constraint-guided dynamic reconfiguration in sensor networks

Kogekar, Sachin; Neema, Sandeep; Eames, Brandon; Koutsoukos, Xenofon; Lédeczi, Ákos; Maróti, Miklós

doi:10.1145/984622.984677

Cited by 41 publications

(34 citation statements)

References 15 publications

(16 reference statements)

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“…The approach is well suited for coping with high number of artifacts but the real-time aspect is not well-developed. A formalization of the reconfiguration as a constraint satisfaction problem was proposed in [56,34,38]. The design space is (at least partially) represented and its design constraints are explicitly stated.…”

Section: Approaches To Runtime Adaptivitymentioning

confidence: 99%

“…To keep the development efforts on a reasonable level both design and implementation support is needed. Many of the runtime reconfiguration approaches cited propose an architectural methodology, design tool set and runtime support, e.g., [17,31,30,56,28,60,34,35]. A common feature of these efforts is to support the system developer with application independent reconfiguration functionalities, which can be parameterized according to the concrete needs of the application at hand.…”

Section: Implementation Of Runtime Reconfigurationmentioning

confidence: 99%

“…This adds an extra layer of complexity to the systems, e.g., implementing distributed snap-shot algorithms, leader election and distributed reasoning/planning, that may demand resources beyond the capabilities of the nodes. A work-around is to give up the fully distributed implementation of the reconfiguration and assign the most demanding functionalities to (dedicated) powerful nodes, as proposed in [31,34,56]). The monitoring information is then forwarded to the reconfiguration node(s) where a new configuration is determined.…”

Section: Implementation Of Runtime Reconfigurationmentioning

confidence: 99%

See 2 more Smart Citations

Low-Power Solutions for Wireless Passive Sensor Network Node Processor Architecture

Sai¹,

Ogirala²,

Mickle³

2012

Intelligent Sensor Networks

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Distributed solutions for signal processing techniques are important for establishing large-scale monitoring and control applications. They enable the deployment of scalable sensor networks for particular application areas. Typically, such networks consists of a large number of vulnerable components connected via unreliable communication links and are sometimes deployed in harsh environment. Therefore, dependability of sensor network is a challenging problem. An efficient and cost effective answer to this challenge is provided by employing runtime reconfiguration techniques that assure the integrity of the desired signal processing functionalities. Runtime reconfigurability has thorough impact both on system design, implementation, testing/validation and deployment. The presented research focuses on the widespreaded signal processing method known as state estimation with Kalman filtering in particular. To that extent, a number of distributed state estimation solutions that are suitable for networked systems in general are overviewed, after which robustness of the system is improved according to various runtime reconfiguration techniques.

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Section: Approaches To Runtime Adaptivitymentioning

confidence: 99%

Section: Implementation Of Runtime Reconfigurationmentioning

confidence: 99%

Section: Implementation Of Runtime Reconfigurationmentioning

confidence: 99%

See 1 more Smart Citation

Low-Power Solutions for Wireless Passive Sensor Network Node Processor Architecture

Sai¹,

Ogirala²,

Mickle³

2012

Intelligent Sensor Networks

View full text Add to dashboard Cite

show abstract

“…In other words, the application requires the gathering rate, node deployment, and the measurement accuracy of sensor nodes related to the application-level QoS. Kogekar et al [7] presented a dynamic reconfiguration method in wireless sensor networks to guarantee application-level QoS under energy-constrained condition. However, QoS guarantees in application layer of MSNs have not been addressed.…”

Section: Qos Guarantees In Application Layermentioning

confidence: 99%

A Self-Adaptive QoS Guarantee Scheme for Multimedia Sensor Networks

Sun

Liu

2010

International Journal of Distributed Sensor Networks

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In multimedia sensor networks, there may exist simultaneously two streams: end-to-end stream and event-to-sink stream. It brings a new set of challenges for QoS guarantees in multimedia transmission. In this paper, we first present a self-adaptive QoS guarantee scheme based on two-layer feedback. In transport layer, we partition network into 10 typical states and design a transport protocol, which makes the state transition to the optimal one. Moreover, we design a revenue structure of media stream to describe the relation between QoS and multimedia capturing approaches in the application layer, thus evaluating the optimal scheme of capturing multimedia according to multimedia packet generation ratio calculated by transport layer. A series of simulation experiments using NS2 are performed to demonstrate the effectiveness of our proposed scheme.

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“…Dynamic software reconfiguration in sensor networks has been achieved in [28] by expressing system requirements as constraints on design space qualityof-service parameters. A run-time search of the design space is made possible by situating the reconfiguration controller on a powerful base station, a strategy which cannot be realized in resource-constrained sensor nodes.…”

Section: Related Workmentioning

confidence: 99%

OASiS: A Service-Oriented Architecture for Ambient-Aware Sensor Networks

Koutsoukos

Kushwaha

Amundson

et al. 2008

Composition of Embedded Systems. Scientific and Industrial Issues

Self Cite

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Abstract. Heterogeneous sensor networks are comprised of ensembles of small, smart, and cheap sensing and computing devices that permeate the environment, as well as resource intensive sensors such as satellite imaging systems, meteorological stations, and security cameras. Emergency response, homeland security, and many other applications have a very real need to interconnect these diverse networks and access information in real-time. Web service technologies provide well-developed mechanisms for exchanging data between heterogeneous computing devices, but they cannot be used in resource-constrained wireless sensor networks. This paper presents OASiS, a lightweight service-oriented architecture for sensor networks, which provides dynamic service discovery and can be used to develop ambient-aware applications that adapt to changes in the network and the environment. An important advantage of OASiS is that it allows seamless integration with Web services. We have developed a middleware implementation that supports OASiS, and a simple tracking application to illustrate the approach. Our results demonstrate the feasibility of a service-oriented architecture for wireless sensor networks.

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Constraint-guided dynamic reconfiguration in sensor networks

Cited by 41 publications

References 15 publications

Low-Power Solutions for Wireless Passive Sensor Network Node Processor Architecture

Low-Power Solutions for Wireless Passive Sensor Network Node Processor Architecture

A Self-Adaptive QoS Guarantee Scheme for Multimedia Sensor Networks

OASiS: A Service-Oriented Architecture for Ambient-Aware Sensor Networks

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