## 1 Introduction  
Even though Sensor Nodes (SNs) may link directly to the processing sinks through local area networks [1], extending these SNs to gather data and transmit them to a central sink is more useful because future applications may demand hundreds or thousands of SNs to be deployed, which are often used in remote and inaccessible regions. A single SN may not only have a sensing capability but also processing, communications and memory units [2], which means that a SN can perform data collection, in-network processing and fusion of its own and other SNs' information. When many SNs join to observe an enormous physical environment thus they form what is termed a Wireless Sensor Network (WSN). WSNs have many applications such as environmental monitoring, health care, security, tracking events and industrial automation [1]. Figure 1 shows a typical wireless sensor network. Data routing is a very critical process in WSNs due to the communications range constraints [3]. Therefore, it is preferable to forward packets from the collection area to the sink or base station by multiple hops in order to reduce the SNs' energy consumption. Consequently, while designing a routing protocol, energy awareness should be taken into consideration such that the battery power is utilized efficiently in order to prolong the lifetime of both nodes and network. Moreover, distributing traffic load across multi-paths balances their energy usage and optimizes WSN throughput. By avoiding frequent use of some nodes it prevents the partitioning of WSN which shortens its life span. Hence this proposed method ensures that the SNs will drain their batteries evenly across the network. There are many challenges and constraints between WSNs and other distributed networks despite their similarities. These constraints affect the design of WSN; this leads to the need to develop protocols that consider these constraints in order to work in WSN environments. The restriction is most often associated with the design of SNs with limited battery power [3,4]. Typically, they are equipped with batteries that have to be replaced or replenished, if they are exhausted. In most cases, it is very difficult to do this, especially in harsh or remote areas, therefore, it is very important to manage the energy consumption in order to conserve energy and ensure longer survival. Therefore, SNs should cooperate and adapt to failures and changes in the phenomena without any external intervention. Routing protocols are an active research topic in sensor networks, and many such techniques have been published [5]. Some of these routing results from the adaptation of the conventional routing methods which are not appropriate for wireless networks because of resource constraints and  
Figure 1: Typical wireless sensor network. frequently changing topology. Due to these challenges new techniques must be adopted to cope with them. Biological inspiration (BI)-based techniques [6], define a new set of rules that can be adapted for WSNs in terms of gathering the food and communications among the species such as ants, bees and birds. The basic idea is that these BIs have to be adjusted to develop new protocols for optimizing and managing sensor networks. Some of these schemes are inspired by the foraging activities of ants. The main reason is that these insects act as a collective unit to resolve routing challenges. They go around to discover and establish routes used by individual ants to efficiently move forward and backward from the nest toward the target food [7]. These routes arise from the cooperative connections of the numerous ant agents during the routes sampling to notify the others about their properties indirectly. The searching behavior of ant agents proves to be adaptive to ambient changes with more scalability. The majority of routing protocols for WSNs aim at decreasing the energy usage of sensor nodes by either explicitly taking energy into account during the route selection or by optimizing some metrics.