A peer-to-peer bandwidth allocation scheme for sensor networks

A peer-to-peer bandwidth allocation scheme for sensor networks
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  A Peer-to-Peer Bandwidth Allocation Scheme for Sensor Networks Luca Caviglione * , Franco Davoli +  University of Genoa – Department of Communications, Computer and Systems Science (DIST) Via Opera Pia 13, 16145 Genova (Italy) Phone: +39-010-3532202, Fax: +39-010-3532154 e-mail: { * , + } Abstract  Nowadays, both bandwidth allocation schemes and Bandwidth on Demand (BoD) schemes are widely adopted. Besides, in the modern Internet there is the tendency toward an even more distributed architectural approach. Actually, decentralized architectures are gaining more and more popularity.  Peer to peer (p2p) applications and their communication paradigm are becoming popular. P2p networking allows obtaining a redundant architecture that reacts well against failure. Based upon p2p  principles, this paper introduces a novel algorithm for configuring and managing bandwidth in a  sensor network. Keywords : p2p, sensor networks, bandwidth on demand (BoD), distributed algorithm, middleware I. Introduction Many of the applications adopted in the modern Internet rely on a client-server framework. Usually, a centralized entity manages requests, processes them by applying some kind of policy, and then sends  back an answer to the srcinal requestor. This approach is simple and easy to understand, but centralized architectures introduce many hazards: there is a single point of failure and the architecture does not scale well. Moreover, there are some problems concerning both performance and throughput  bottlenecks: when a single centralized server cannot handle high client load, a common solution is to use a cluster of machines allowing a more transactional throughput. The antithetical approach is the  distributed one: there are no centralized entities, but the functionalities are spread among all the network participants. The exasperation of this concept brings to p2p networking [1], where all the hosts have the same capabilities and the same responsibilities. To emphasize the aspect, all the entities involved in this kind of network are named peers. This networking paradigm is becoming adopted in different fields, such as distributed computing, instant messaging and GRID computing [2]. However,  p2p networking introduces some problems: the topology is quite trivial, and the lack of a hierarchical organization brings to major difficulties in developing any kind of algorithms. As previously stated, there are no “ well known nodes ” (in a client-server scenario, the server is the known service provider node): functionalities are shared across the network. This characteristic introduces a problem related to information delocalization, leading to a situation where it is impossible to determine the peer that contains information of interest. Due to this fact, to perform content searches (i.e., services or resources), many p2p protocols use a controlled broadcast algorithm. The most popular methodology is  based on the expanding ring principle. The queries are generated and associated to a given value of time-to-live (TTL) and then they are broadcast to the network. Every peer that receives that query will analyze it and send back an answer. The TTL is decremented by one and, if the TTL value differs from zero, the query is routed to the other reachable peers. The process is iterated until TTL reaches the zero value. To reduce the localization indeterminacy, a widely adopted solution consists of leaving the pure  p2p network architecture in advantage of a mediated p2p topology: some peers act as “ mediation  points ”, allowing a simplified network management. One of the key problems in modern device-networks concerns the management of the bandwidth available at the physical level. This is not the classical Quality of Service (QoS) problem [3] [4]. QoS techniques are powerful, but resource intensive, and rely on a well-organized network infrastructure. Sensors are usually equipped with low computational resources and sophisticated resource reservation  policies are often not applicable. Sensor networks are based on wireless technology: among others, the  most adopted one seems to be the IEEE 802.11 [5] family. Sensors are added or removed “on the fly”. Moreover, a sensor might stop working properly at any time. In addition, sensors often rely on battery  power supply and, consequently, battery life is a critical issue. Classical proactive protocols might waste power, shortening sensors’ lifetime. BoD-based algorithms are reactive technologies that perform actions only in response to a particular event (e.g., a bandwidth request or a critical topology change). Moreover, since a sensor might stop working due to power shortage at any time, distributing BoD functionalities among all the sensors will improve fault tolerance. Finally, sensor networks are most of the time based on wireless protocol using a broadcast scenario. The proposed algorithm solves the problem of bandwidth reservation and utilization in a low mobility context, allowing coordinated bandwidth usage and releasing resources when they are no longer needed. The paper is structured as follows: Section II introduces the operative scenario. Section III discusses the protocol architecture and the proposed algorithm. Section IV reports simulation results and, finally, Section V contains the conclusions and indications for future works.  II. Operative Scenario As previously stated, the proposed algorithm is deployed and tested in a scenario concerning a wireless sensor network. In this perspective, a “static” sensor network is assumed: the node mesh will not change its topology during its lifetime (nodes may turn on and off, but no roaming through multiple services areas is considered). In particular, the algorithm relies on information routability: a proper routing algorithm is assumed (e.g., AODV [6]), that allows delivering proper control information. Generally, a sensor network relies on a quite simple architecture and a broadcast-based routing strategy is often adopted. In addition, a sensor, which is a node of the networked infrastructure, should be added or removed during the network lifetime. Sensors are usually simple devices: an end-to-end bandwidth reservation or signaling strategy a la  RSVP [7] is difficult to implement on devices with limited resources and capabilities. In addition, there are many concerns about configuration issues. In many circumstances, sensors are not reachable from the outside: they are masqueraded by a special gateway that collects data (e.g. a DB-node) and then sends data remotely through the Internet. Sensor networks are often deployed by using a private IP based scheme, jointly with a NAT-based [8] device: the gateway should also implement IP address conversion, acting as a Network Address Translator (NAT). The gateway performs also both medium and protocol conversions. For instance, the sensor network communicates to a remote center via wired technology or via satellite by exploiting a proper  protocol solution [9]. In this perspective, where sensors are not publicly addressable, an auto-configuration scheme is necessary. The proposed algorithm is intended to be operative without any external help. Only a certain configuration is required; if some policy is requested, it must be “hardcoded” within the middleware or simply stored in a configuration file. The proposed framework is not zero-configurable (in the sense of the ZeroConf standard [10]), but it requires a minimal configuration effort.  III. Protocol Architecture Figure 1 depicts the layered protocol architecture and the protocol interfaces adopted. Each node implements the reference stack. There are two kinds of interfaces: Transport Access Points (TAP) and Bandwidth Access Points (BAP). TAPs are responsible of providing a standard communication path  between the application layer and the transport layer, while BAPs are responsible of communication  between the application and the middleware layer, implementing the BoD algorithm. Sensors are simple devices and often rely on simple software implementations. Therefore, most of the time the layered architecture is never fully implemented. In this perspective, the reference model might be too complex: the middleware layer should be merged with others and the adopted interfaces should be reduced to a library call rather than a full software entity. Nowadays, many embedded devices implement a full TCP/IP protocol stack [11]. Many of them adopt a “stateless” version of the TCP [12] allowing a fully compatible TCP version but with a simplified behavior. Figure 1. Layered Protocol Architecture. The Bandwidth Allocation Middleware offers only a bandwidth allocation service: allocation related control traffic is exchanged among the BAPs. As depicted in Figure 1, middleware traffic is delivered  by using transport services: middleware is “wired” within the transport layer via TAPs. By doing so, Allocation Services Physical Data Link  Network Transport Bandwidth allocation middleware Application Transport Services Transport Services Transport Access Point Bandwidth Access Point
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