24-12-2012, 12:36 PM
Exploring efficient Adaptive Reprogramming by Optimized Multihop Code Generation in Ad Hoc Wireless Network
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Introduction :
Typical wireless sensor network (WSN) consists of a large number of small-sized battery-powered sensor nodes that integrate sensing, computing, and communication capabilities. In most applications sensor networks are deployed once in the designated area like Geophysical /structural/habitat monitoring, security surveillance, disaster area or battlefield information collection, and pervasive computing, will be expected to operate for extended periods of time, without any human intervention. Management and maintenance tasks of WSNs are challenging, as time goes by, the existing application procedures in sensor nodes may not match the current mission, because of the changes in the environment and user’s needs, enabling sensor networks to be reprogrammable is a way to address such challenges.
There are many reasons why reprogrammability is in a significant need for deploying WSNs as follows. It is a crucial issue for the acceptance of WSNs in most major fields. Reprogrammability, also known as reconfiguration or retasking, refers to as the capacity of being able to deploy applications dynamically to WSNs without the need of manual intervention Wireless sensor networks need an efficient and reliable reprogramming service to facilitate management and maintenance tasks. Software already installed in sensor nodes may need to be updated with new functionalities or features. Existing applications may be found to have bugs that need to be fixed on the fly . Parameters and settings may have to be changed over time. More importantly, during the lifecycle of a deployed WSN, it is quite common that new users come with new tasks to be executed via an existing WSN.
Traditional ways of manually reprogramming sensors are costly, labor intensive or even impossible since each node has to be collected from the field and physically attached to a computer to “burn” new codes. In contrast to code dissemination, code acquisition is initiated from individual sensors to fetch and install program modules from the network dynamically and on demand. It enables sensor nodes to self-reprogram so that they can adapt to changing tasks and evolving environments. Due to capacity constraints of sensor nodes, a monolithic program with too many functions cannot be fitted into the memory. In addition, applications may need extra modules to handle unforeseen events.
Vulnerabilities that complicate design and deployment
This section discusses the limitations that complicate the routing protocols, security design and deployment in sensor networks. It is important to understand the constrained capabilities of sensor nodes performance against sensor nodes' limitations.
1. Hostile Environment
Sensor networks can be deployed in remote or hostile environments such as battlefields. In these cases, the nodes cannot be protected from physical attacks, since anyone could have access to the location where they are deployed. An adversary could capture a sensor node or even introduce his own malicious nodes inside the network. If the latter is the case, the adversary’s aim is to trick the network into accepting his nodes as legitimates.
2. Random topology
Most of the time, deploying a sensor network in a hostile environment is done by random distribution, i.e. from an airplane. Therefore, it is difficult to know the topology of sensor networks a priori. In these situations, it is hard to store various encryption keys on nodes in order to establish encryption among a group of neighbors, since the neighborhood cannot be known a priori.
The challenge is to design key agreement protocols that do not require certain nodes to be neighbors of some other nodes, and also do not require encryption keys to be stored on sensors before deployment. Appropriate key distribution algorithms must be designed along a flexible WSN architecture to securely provide encryption keys in real time.
3. Power restrictions
The power restrictions of sensor nodes are raised due to their small physical size and lack of wires. Since the absence of wires results in lack of a constant power supply, not many power options exist. Sensor nodes are typically battery-driven. However, because a sensor network contains hundreds to thousands of nodes, and because often WSN are deployed in remote or hostile environments, it is difficult to replace or recharge batteries. The power is used for various operations in each node, such as running the sensors, processing the information gathered and data communication.
Communication between sensor nodes consumes most of the available power, much more than sensing and computation. Power limitations greatly affect security, since encryption algorithms introduce a communication overhead between the nodes; more messages must be exchanged, i.e. for key management purposes, but also messages become larger as authentication, initialization and encryption data must be included.
4. Limited Computational power
In the case of computational power, computations are linked with the available amount of power. As you may understand, since there is a limited amount of power, computations are constrained also. Although it is acknowledged that sensors are not expected to have the computing power of workstations or even mobile handheld devices, researchers and developers are greatly concerned with the issue.
5. Error-prone wireless medium.
Since sensor networks can be deployed in different situations, the requirements of each different application may vary significantly. Researchers must take into consideration that the wireless medium can be greatly affected by noisy environments, and thus the signal attenuates in regard to the noise. Note that an adversary can intentionally interfere and cause enough noise to affect the communication. In an environment such as healthcare, it is vital to ensure that communication is on time to respond to emergencies.
6 .Fault tolerance and adaptability
If a sensor node fails due to a technical problem or consumption of its battery, the rest of the network must continue its operation without a problem. Researchers must design adaptable protocols so that new links are established in case of node failure or link congestion. Furthermore, appropriate mechanisms should be designed to update topology information immediately after the environment changes so as to minimize unnecessary power consumption.