24-01-2013, 12:19 PM
Routing in Wireless Sensor Networks Using an Ant Colony Optimization (ACO) Router Chip
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Abstract:
Wireless Sensor Networks consisting of nodes with limited power are deployed
to gather useful information from the field. In WSNs it is critical to collect the information
in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based
optimization technique, is widely used in network routing. A novel routing approach using
an Ant Colony Optimization algorithm is proposed for Wireless Sensor Networks
consisting of stable nodes. Illustrative examples, detailed descriptions and comparative
performance test results of the proposed approach are included. The approach is also
implemented to a small sized hardware component as a router chip. Simulation results
show that proposed algorithm provides promising solutions allowing node designers to
efficiently operate routing tasks.
Introduction
Due to advances in low-power wireless communications, low-power analog and digital electronics,
the development of low-cost and low-power sensor nodes that are small in size has received increasing
attention. Sensor nodes have the ability to sense the environment nearby, perform simple computations
and communicate in a small region. Although their capacities are limited, combining these small
sensors in large numbers provides a new technological platform, called Wireless Sensor Networks
(WSNs). WSNs provide reliable operations in various application areas including environmental
monitoring, health monitoring, vehicle tracking system, military surveillance and earthquake
observation [1-2].
Although WSNs are used in many applications, they have several restrictions including limited
energy supply and limited computation and communication abilities. These limitations should be
considered when designing protocols for WSNs. Because of these considerations specific to WSNs,
many routing schemes using end-to-end devices and MANETs [3] are inappropriate for WSNs.
In sensor networks, minimization of energy consumption is considered a major performance
criterion to provide maximum network lifetime. When considering energy conservation, routing
protocols should also be designed to achieve fault tolerance in communications. In addition, since
channel bandwidth is limited, protocols should have capability of performing local collaboration to
reduce bandwidth requirements [4].
Proposed WSN Routing Scheme
A WSN routing task which consists of stable or limited mobile nodes and a base station is
considered as the problem. To achieve an efficient and robust routing operation, major features of
typical WSNs are taken into consideration. First, failures in communication nodes are more probable
in WSNs than classical networks, as nodes are often located in unattended places and they use a
limited power supply. Therefore the network should not be affected by a node’s failure and should be
in an adaptive structure to maintain the routing operation. This is performed by sustaining different
paths alive in a routing task. A node transferring data to the base sends it in divided parts (as data
packages) using different paths. When a failure occurs in a path, the associated data package cannot
arrive at the base. To achieve guaranteed delivery, acknowledgement signals are used. In the case of an
absent acknowledgement for a data package, the source node resends that package to a different path.
By performing acknowledgement-associated data transfers and sustaining different paths alive, routing
becomes more robust. It is obvious that some paths in this type of network would be shorter, allowing
for lower energy costs. Transmission on these paths should be more frequent to reduce the total cost of
energy consumed using these paths. In other words, more data packages should be transferred along
shorter paths to achieve a lower energy consumption
Simulations and Results
In this section, we present the performance results of the simulation experiments. To accomplish the
experiments, a parallel discrete event-based platform was developed in MATLAB. In the simulation, a
free space radio propagation model is used. In order to verify the success of the proposed approach, an
energy-efficient ant-based routing algorithm EEABR [17], a well known ACO based WSN routing
algorithm, was used to make comparisons. The simulation is capable of running packet level
experiments, and uses parameter values of a hardware named MICAz mote [21], specifications of
which are given in Table 1. Experimental results are obtained for the two algorithms which are the one
proposed in the approach described in Section 2 and the EEABR algorithm in [17]. The ACO
parameters and the specifics of hardware are set to the values specified in Section 2.1 and Table 1
Implementation of ACO Algorithm
Because of space constraints on the sensor nodes, designers should consider the space requirements
of the hardware components they use. A small sized chip having the routing capability mentioned so
far offers advantageous solutions for the design stage. By using a separate chip, the full computational
power of the main processor could be used for sensor node tasks (e.g. sensing, data processing)
specific to itself instead of allocating some of that power to relatively complex routing tasks.
Moreover, it is not required that node designers code routing protocols which need detailed knowledge
of the issue. Instead, a hardware component ready to perform dynamic routing operations is proposed.
Routing tasks are performed under the guidance of the router chip embedded a novel routing protocol
using ACO as designers have no need to know any routing considerations. The chip uses a simple
communication protocol illustrated in detail in Figure 8. In Table 2, the main specifications of this
router chip are given.
Conclusions
In this paper we have presented a new protocol for WSN routing operations. The protocol is
achieved by using an ACO algorithm to optimize routing paths, providing an effective multi-path data
transmission method to achieve reliable communications in the case of node faults. We aimed to
maintain network life time at a maximum, while data transmission is achieved efficiently, so an
adaptive approach is developed according to this goal. The proposed approach is compared to a wellknown
ant based algorithm named EEABR using an event-based simulator. The results show that our
approach offers significant reductions of energy consumption which is used as a performance metric
for different sized WSNs. We also implemented our approach on a small sized hardware component
requiring minimum connections suitable for tiny node designs and we developed an easy method for
handling the routing tasks by using the proposed router chip. We also tested the ACO algorithm
running on the router chip and obtained its performance results, including response times of the chip.
Response time of the header request for the routing operation would be satisfactory for many WSNs
where transmission speed is not essential. The proposed ACO approach for WSN routings and its
hardware implementation seem to be a promising solution for node designers. As future work, it is
planned to improve our routing approach to be effective in proper WSN settings, including nodes
having high mobility. The improved approach will also be studied in network types that include
multiple sink nodes.