Efficient algorithms for neighbor discovery in wireless networks
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E1. The paper proposes and analyzes several algorithms for neighbor discovery in wireless networks. It presents an ALOHA-like algorithm for when nodes cannot detect collisions and a receiver feedback-based algorithm when they can. E2. It then analyzes neighbor discovery in a multihop setting, establishing an upper bound on the running time of the ALOHA-like algorithm and a lower bound on the running time of any randomized algorithm. E3. The paper aims to develop algorithms that do not require nodes to know the number of neighbors or be synchronized, and that allow asynchronous starting and determine when to terminate discovery.
Efficient algorithms for neighbor discovery in wireless networks
- 1. Efficient Algorithms for Neighbor Discovery in Wireless Networks ABSTRACT: Neighbor discovery is an important first step in the initialization of a wireless ad hoc network. In this paper, we design and analyze several algorithms for neighbor discovery in wireless networks. Starting with a single-hop wireless network of nodes, we propose a ALOHA-like neighbor discovery algorithm when nodes cannot detect collisions, and an order-optimal receiver feedback-based algorithm when nodes can detect collisions. Our algorithms neither require nodes to have a priori estimates of the number of neighbors nor synchronization between nodes. Our algorithms allow nodes to begin execution at different time instants and to terminate neighbor discovery upon discovering all their neighbors. We finally show that receiver feedback can be used to achieve a running time, even when nodes cannot detect collisions. We then analyze neighbor discovery in a general multihop setting. We establish an upper bound of on the running time of the ALOHA-like algorithm, where denotes the maximum node degree in the network and the total number of nodes. We also establish a lower bound of on the running time of any randomized neighbor discovery algorithm. Our result thus implies that the ALOHA-like algorithm is at most a factor worse than optimal.
- 2. EXISTING SYSTEM: 1) Neighbor discovery needs to cope with collisions. Ideally, a neighbor discovery algorithm needs to minimize the probability of collisions and, therefore, the time to discover neighbors. 2) In many practical settings, nodes have no knowledge of the number of neighbors, which makes coping with collisions even harder. 3) When nodes do not have access to a global clock, they need to operate asynchronously and still be able to discover their neighbors efficiently. 4) In asynchronous systems, nodes can potentially start neighbor discovery at different times and, consequently, may miss each other’s transmissions. 5) Furthermore, when the number of neighbors is unknown, nodes do not know when or how to terminate the neighbor discovery process.
- 3. PROPOSED SYSTEM: In this paper, we present neighbor discovery algorithms that comprehensively address each of these practical challenges under the standard collision channel model. Unlike existing approaches that assume a priori knowledge of the number of neighbors or clock synchronization among nodes, we propose neighbor discovery algorithms that: P1 do not require nodes to have a priori knowledge of the number of neighbors; P2 do not require synchronization among nodes; P3 allow nodes to begin execution at different time instants; P4 enable each node to detect when to terminate the neighbor discovery process. To the best of our knowledge, our work provides the first solution to the neighbor discovery problem that satisfies all of the properties P1–P4. Our approach is to start with a single-hop wireless network in which nodes are synchronized and know exactly how many neighbors they have. As we will see, the analysis in such a simplistic setting yields several valuable insights about the neighbor discovery problem. These insights allow us to progressively relax each of the assumptions leading to a complete and practical solution to the neighbor discovery problem in a multihop network setting.
- 7. SYSTEM CONFIGURATION:- HARDWARE REQUIREMENTS:- Processor - Pentium –IV Speed - 1.1 Ghz RAM - 512 MB(min) Hard Disk - 40 GB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - LCD/LED SOFTWARE REQUIREMENTS:- Operating System : LINUX Tool : Network Simulator-2
- 8. Front End : OTCL (Object Oriented Tool Command Language) REFERENCE: Sudarshan Vasudevan, Micah Adler, Dennis Goeckel, and Don Towsley, “Efficient Algorithms for Neighbor Discovery in Wireless Networks”, IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 21, NO. 1, FEBRUARY 2013.