# Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things
### Sensor Network Clustering  
The issue of energy efficiency for wireless sensor networks has attracted much interest in the research community, as these networks are built around tiny nodes with limited processing, minimum memory footprint and low communication capabilities. Sensor network clustering is an energy-aware traffic engineering method, which aims to maximize the lifetime of a sensor network, by structuring the sensor network into clusters and assigning \"cluster head\" and \"cluster member\" roles to the sensor nodes. This enables multi-hop communication, data aggregation and fusion within a cluster, in order to decrease the number of messages routed by the sensor network and essentially reducing the number of hops traversed by the sensor readings from the source to the sink node. This is implemented by subdividing a sensor network into a hierarchy of sensor clusters, each containing a cluster head. The sensor nodes are organized into cluster members and cluster heads depending on different performance parameters, such as their residual node's energies. The cluster heads play the role of collecting, aggregating and processing data, while the cluster members are assigned the minimal functioning roles of sensing and forwarding. By producing several points of data aggregation and processing in the core of the network, in-network processing is promoted, and the network edge is left light. This model moves away from the Internet paradigm, which uses intelligent edges to produce data, which are forwarded by a dumb core. Low energy adaptive clustering hierarchy (LEACH) [10] and LEACH-centralized (LEACH-C) [11] are two clustering algorithms that have been proposed to address the energy efficiency issue in wireless sensor networks. While LEACH builds upon a distributed clustering model where the sensor nodes independently determine their role based on a probabilistic value or residual energy, LEACH-C uses a centralized model, where the gateway attached to the sink node uses _a priori_ knowledge of the geographical position, residual energy and neighbor information of all sensor nodes to select the cluster heads. However, both LEACH and LEACH-C are built around a homogeneous service architecture, where all sensor motes are assumed to be made of the same sensor fabric and are expected to deliver equal service and exhibit the same power consumption profile for all nodes. This discounts the energy required to deliver these services, thereby leaving the energy consumption equation unsolved. DECSA [12] is an improvement of the the LEACH protocol, which considers both the residual energy of nodes and the distance between nodes when selecting cluster heads (CHs) during cluster formation. It is based on a three-level hierarchical structure that divides a sensor network into four types of sensors: common sensor nodes (SN), cluster head node (CH), base station cluster head (BCH) and base station (BS). In DECSA, the selection of CHs depends on a random number generated by each sensor node. This random number must be less than a predefined threshold. The sensor node with the highest probability becomes a CH depending on the node's residual energy. DECSA avoids direct communication between the CH and the base station when their communication distance is greater than a given threshold value. It reduces energy consumption by 40%, prolongs the network's lifetime by 31% and performs better compared to the LEACH protocol. However, the cluster heads selected based on this approach are not uniformly distributed within the network, and there is a high probability that the selected CHs will be on the same side of the network. This might result in an increase in energy consumption. MOCRN [13] is another recent improvement of the LEACH protocol, which is based on the minimum separation distance between the cluster heads. Initially, MOCRN randomly selects K nodes as its cluster heads (CHs). Every node selected as a CH sends its information to the next node within its transmission range.