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WIRELESS SENSOR NETWORKS MANAGEMENT

Budhaditya Deb and Badri Nath

Sensor networks have fundamentally different architecture than normal wired data networks. They are highly constrained in resources, have multihop wireless connectivity and form adhoc networks with random deployment in possibly unmanned terrain. Sensor Networks also introduce a new paradigm of statistical networking. The individual node behavior could be highly irregular although the network has statistically predictable behavior. Even though management of sensor networks is a non-trivial task, this area has been left largely untouched. Algorithms for sensor network measurements and performance analysis do not exist. Our research is motivated towards finding efficient solutions for Sensor Network Management [sNMP]. Sensor Network management protocols thus could be significantly different from SNMP for the Internet and pose new theoretical problems and practical challenges. 

Design of sNMP is divided in the following categories

  1. Defining SNMP framework
  • Defining various models for representing the current Network state and has to incorporate the specific features described above.
  • Defining various Network Management Functions, which may be required for sensor networks.
  1. Design algorithms and tools for retrieving network state and maintenance of network using the network management functions
  2. Design algorithms and tools for retrieving network state and maintenance of network using the network management functions.
  3. Creating a test bed of sensor network using the currently available wireless sensor nodes, conduct experiments for the sNMP.

Papers

TITLE: On the Node Scheduling Approach of Topology Control in Ad hoc Networks , In MOBIHOC 2005 (Urbana Champagne Illinois).

AUTHORS: Budhaditya Deb, Badri Nath 

ABSTRACT:
In this paper, we analyze the node scheduling approach of topology control in the context of reliable packet delivery. In node scheduling, only a minimum set of nodes needed for routing purposes (usually determined by a minimum connected dominating set, MCDS) are kept active. However, a very low density resulting from switching off nodes can adversely affect the performance of data delivery due to three factors. First, our analysis shows that at low density, the average path length increases by a factor more than previously thought. Second, protocols such as the Hop-By-Hop Broadcast (HHB) reliability scheme (which relies on high network degree for optimum performance) suffer. Third, with limited buffers at nodes, the overhead is more pronounced to the extent of making the network unstable. Using probabilistic models, we derive the relationship between network density and overhead based on the above factors and find the density conditions for minimum power consumption.  We also propose a, fully distributed and message-optimal node scheduling algorithm with a constant approximation bound based on the concept of Virtual Connected Dominating Sets. The scheme can asymptotically achieve optimal density conditions while adapting to different network parameters.
 

TITLE: Multi-Resolution State Retrieval in Sensor Networks , First IEEE Workshop on Sensor Network Protocols And Applications (SNPA) Anchorage 2003

TITLE Also As: STREAM: Sensor Topology Retrieval at Multiple Resolutions , To Appear in Journal of Telecommunications, Kluwer Publications, Special Issue on Wireless Sensor Networks.

AUTHORS: Budhaditya Deb, Sudeept Bhatnagar, Badri Nath

ABSTRACT:  dcs-tr-478
Large-scale sensor networks require mechanisms to extract topology information that can be used for various aspects of sensor network management. It is critical for any topology discovery algorithm in sensor networks to adhere to the resource constraints of bandwidth and energy. In this paper, we describe a distributed parameterized algorithm for Sensor Topology Extraction at Multiple Resolutions (STEM), which makes a tradeoff between topology details and resource expended.  The algorithm retrieves network state at multiple resolutions at a proportionate communication cost.We also define various classes of topology queries and show how the parameters in the algorithm can be used to support queries specific to sensor networks. We show that the topology determined, albeit at a low resolution, is sufficient for approximating actual network properties.Finally we show how STEM can be used for general-purpose multi-resolution information retrieval in sensor networks.
 

Title : A Topology Discovery Algorithm for Sensor Networks with Applications to Network Management , DCS Technical Report DCS-TR-441, Rutgers University May 2001 
To appear in IEEE CAS workshop, September 2002 (Short Paper)
Authors: Budhaditya Deb, Sudeept Bhatnagar & Badri Nath

Abstract:
In this paper we describe a topology discovery algorithm (TopDisc) for wireless sensor networks with its applications to network management. The algorithm finds a set of distinguished nodes, using whose neighborhood information we can construct the approximate topology of the network. Only these distinguished nodes reply back to the topology discovery probes, thereby reducing the communication overhead of the process. These nodes logically organize the network in the form of clusters comprised of nodes in their neighborhood. TopDisc forms a Tree of Clusters (TreC) rooted at the monitoring node, which initiates the topology discovery process. We show how managing a complex network of sensor nodes is simplified using a TreC. This organization is used for efficient data dissemination and aggregation, duty cycle assignments and network state retrieval.  The mechanisms proposed are completely distributed, use only local information and are highly scalable.