Sensors_**2010**, _10_, 8761-8781; doi:10.3390/s100908761  
_Sensors_  
**ISSN 1424-8220**  
www.mdpi.com/journal/sensors  
_Article_  
**Load-Adaptive Practical Multi-Channel Communications in Wireless Sensor Networks**  
**[PERSON], [PERSON], [PERSON] \({}^{\star}\) and [PERSON]**  
Department of Computer Engineering, Kyung Hee University, 1 Seocheon, Giheung, Yongin,  
Gyeonggi 449-701, Korea; E-Mails: [EMAIL_ADDRESS] (M.S.I. );  
[EMAIL_ADDRESS] (M.M.A. ); [EMAIL_ADDRESS] (S.L.) \({}^{\star}\) Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel. : +82-31-201-2532; Fax: +82-31-204-9082. _Received: 19 August 2010; in revised form: 14 September 2010 / Accepted: 15 September 2010 / Published: 21 September 2010_  
**Abstract:** In recent years, a significant number of sensor node prototypes have been designed that provide communications in multiple channels. This multi-channel feature can be effectively exploited to increase the overall capacity and performance of wireless sensor networks (WSNs). In this paper, we present a multi-channel communications system for WSNs that is referred to as load-adaptive practical multi-channel communications (LPMC). LPMC estimates the active load of a channel at the sink since it has a more comprehensive view of the network behavior, and dynamically adds or removes channels based on the estimated load. LPMC updates the routing path to balance the loads of the channels. The nodes in a path use the same channel; therefore, they do not need to switch channels to receive or forward packets. LPMC has been evaluated through extensive simulations, and the results demonstrate that it can effectively increase the delivery ratio, network throughput, and channel utilization, and that it can decrease the end-to-end delay and energy consumption. **Keywords:** wireless sensor networks; multi-channel; load detection; channel allocation and deallocationIntroduction  
A wireless sensor network consists of battery-powered sensing devices that transmit their observations to the base station. The sensing nodes have a limited transmission range, so nodes away from the base station deliver their data through intermediate nodes. The data generation rates of the sensing nodes depend on the applications. An elastic application might use varying data rates. For example, a monitoring application generates data at a very low rate in the absence of an event, whereas a particular feature might lead to a huge traffic burst [1]. Because of the limited capacity of nodes, the generated data often exceed the network capacity, leading to congestion and contention loss. A congestion control mechanism alleviates the congestion by restricting the nodes from generating data that the network cannot deliver. This ensures optimum usage of the resources and decreases congestion losses. However, if the application requires higher data rates, a congestion control (or rate control) mechanism cannot meet the demand. Therefore, some works have advocated for increased network resources to avoid congestion and to deliver the required data [2, 3]. On the contrary, recent sensor motes, such as MicaZ [4] and Telos [5], are capable of using a number of channels [6]. A single adapter can use different channels at different times. If nearby nodes use orthogonal channels, multiple nodes can transmit simultaneously, thereby increasing the network capacity. Multi-channel communications can provide the required data delivery without adding extra resources. The use of a single channel is, therefore, not only an under-utilization of the limited resources of WSNs, but it might also hinder the fidelity of the application. To improve the network capacity, many multi-channel medium access control (MAC) protocols have been proposed. These protocols generally assign (as part of the network setup) orthogonal channels to the nodes (either to the senders or the receivers) in a two-hop neighborhood [7, 8, 9].