Delay characterization and performance evaluation of cluster-based WSN with different deployment distributions

• We demonstrated the key role of BS location selection for random topology to fulfill the application mission.
• Delay statistical analysis captures the intrinsic properties of the main delay components.
• Real-time applications should examine the instantaneous delay and not only depend on the average values.
• A tradeoff should be considered between the energy utilization efficiency and the required amount of data/coverage.

Provisioning of quality of service (QoS) is the ultimate goal for any wireless sensor network (WSN). Several factors can influence this requirement such as the adopted cluster formation algorithm. Almost all WSNs are structured based on grouping the sensors nodes into clusters. Not all contemporary cluster formation and routing algorithms (e.g. LEACH) were designed to provide/sustain certain QoS requirement such as delay constraint. Another fundamental design issue is that, these algorithms were built and tested under the assumption of uniformly distributed sensor nodes. However, this assumption is not always true. In some industrial applications and due to the scope of the ongoing monitoring process, sensors are installed and condensed in certain areas, while they are widely separated in other areas. Also unlike the random deployment distributions, there are many applications that need deterministic deployment of sensors like grid distribution. In this work, we investigated and characterized the impact of sensor node deployment distributions on the performance of different flavors of LEACH routing algorithm. In particular, we studied via extensive simulation experiments how LEACH cluster formation approach affects the delay (inter and intra-cluster delay) and energy efficiency expressed in terms of packet/joule for different base station locations and data loads. In this study, we consider four deployment distributions: grid, normal, exponential and uniform. The results showed the significant impact of nodes distribution on the network energy efficiency, throughput and delay performance measures. These findings would help the architects of real time application wireless sensor networks such as secure border sensor networks to design such networks to meet its specifications effectively and fulfill their critical mission.