Architecture and Prototyping of an 802.11 Based Self-Organizing Hierarchical ADHOC Wireless Network (SOHAN)

Ganu, Sachin; Raju, L Raghavendar; Anepu, B.; Zhao, Shenghui; Seskar, Ivan; Raychaudhuri, Dipankar

doi:10.1007/0-387-23072-6_7

Cited by 13 publications

(3 citation statements)

References 3 publications

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“…Representative examples of such hierarchical wireless sensor networks are PASTA(Power Aware Sensing, Tracking and Analysis) [16] mentioned in COSMOS [16] and SOHAN [4]. PASTA is used in We expect that hierarchical sensor networks will be increasingly more utilized in the future as the scale and the requirement of applications increase.…”

Section: Hierarchical Wireless Sensor Networkmentioning

confidence: 99%

“…Representative examples of such hierarchical wireless sensor networks are PASTA(Power Aware Sensing, Tracking and Analysis) [16] mentioned in COSMOS [16] and SOHAN [4]. PASTA is used in military applications for enemy movement surveillance and is configured with the server and about 400 intermediate tier nodes each clustering about 20 sensor nodes.…”

Section: Hierarchical Wireless Sensor Networkmentioning

confidence: 99%

“…However, the definitions of the hierarchical sensor network vary depending on specific environments. Nevertheless, it is a common understanding that a hierarchical sensor network consists of multiple tiers and deploys devices of different capabilities at different tiers [4,17,2]. We define the hierarchical sensor network as in Definition 1.…”

Section: The Hierarchical Sensor Networkmentioning

confidence: 99%

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Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

Lee

Whang

Lim

et al. 2010

IEICE Trans. Inf. & Syst.

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SUMMARYIn this paper, we study the problem of processing continuous range queries in a hierarchical wireless sensor network. Recently, as the size of sensor networks increases due to the growth of ubiquitous computing environments and wireless networks, building wireless sensor networks in a hierarchical configuration is put forth as a practical approach. Contrasted with the traditional approach of building networks in a "flat" structure using sensor devices of the same capability, the hierarchical approach deploys devices of higher-capability in a higher tier, i.e., a tier closer to the server. While query processing in flat sensor networks has been widely studied, the study on query processing in hierarchical sensor networks has been inadequate. In wireless sensor networks, the main costs that should be considered are the energy for sending data and the storage for storing queries. There is a trade-off between these two costs. Based on this, we first propose a progressive processing method that effectively processes a large number of continuous range queries in hierarchical sensor networks. The proposed method uses the query merging technique proposed by Xiang et al. as the basis. In addition, the method considers the trade-off between the two costs. More specifically, it works toward reducing the storage cost at lower-tier nodes by merging more queries and toward reducing the energy cost at higher-tier nodes by merging fewer queries (thereby reducing "false alarms"). We then present how to build a hierarchical sensor network that is optimal with respect to the weighted sum of the two costs. This allows for a cost-based systematic control of the trade-off based on the relative importance between the storage and energy in a given network environment and application. Experimental results show that the proposed method achieves a near-optimal control between the storage and energy and reduces the cost by 1.002 − 3.210 times compared with the cost achieved using the flat (i.e., non-hierarchical) setup as in the work by Xiang et al. key words: hierarchical sensor network, progressive processing, continuous range queries

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Section: Hierarchical Wireless Sensor Networkmentioning

confidence: 99%

“…Representative examples of such hierarchical wireless sensor networks are PASTA(Power Aware Sensing, Tracking and Analysis) [16] mentioned in COSMOS [16] and SOHAN [4]. PASTA is used in military applications for enemy movement surveillance and is configured with the server and about 400 intermediate tier nodes each clustering about 20 sensor nodes.…”

Section: Hierarchical Wireless Sensor Networkmentioning

confidence: 99%

Section: The Hierarchical Sensor Networkmentioning

confidence: 99%

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Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

Lee

Whang

Lim

et al. 2010

IEICE Trans. Inf. & Syst.

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Interworking of Self-organizing Hierarchical Ad Hoc Networks and the Internet

Lee

Rhee

Raychaudhuri

et al. 2006

Computational Science – ICCS 2006

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Self-organizing hierarchical ad hoc network (SOHAN) is a new network architecture that has been proposed to increase the scalability property of flat ad hoc networks. This paper describes how SOHAN interoperates efficiently with the Internet based on IPv6. Procedures for the autoconfiguration of a globally-routable address, routing and gateway discovery are presented. The amount of control overheads is reduced by taking advantage of cross-layer interaction and limited-scope broadcast (LSBC) techniques. Simulation results display SOHAN with the proposed interworking procedures outperforms conventional flat ad hoc networks in interworking with the Internet in terms of throughput capacity and scalability.

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Beacon assisted discovery protocol (BEAD) for self-organizing hierarchical ad-hoc networks

Raju

Ganu

Anepu

et al.

IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.

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Architecture and Prototyping of an 802.11 Based Self-Organizing Hierarchical ADHOC Wireless Network (SOHAN)

Cited by 13 publications

References 3 publications

Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

Interworking of Self-organizing Hierarchical Ad Hoc Networks and the Internet

Beacon assisted discovery protocol (BEAD) for self-organizing hierarchical ad-hoc networks

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