# Location-Based Lattice Mobility Model for Wireless Sensor Networks
## 1 Introduction  
The wireless sensor networks experience problems for applications that require mobility support, such as disaster/earthquake recovery, battlefield surveillance, monitoring and handling animals, and law enforcement situations. These applications require a dynamically adoptable WSN network with mobility support to guarantee reliable communication, reliable network connectivity, low energy consumption and a longer network lifetime [1]. Thus, it is essential to introduce a system that is energy efficient at all levels of the protocol stack. The energy efficiency and scalability of WSNs depend on the mobility variances [2]. As a result, the lack of a robust mobility model results in performance degradation and unpredictable broken links [3]. Furthermore, mobility plays a significant role in identifying the time-based features of network traffic in WSNs that directly affect resource provision structures and enable network designed control. It has been confirmed that high traffic load posed by a single sensor node is narrowly associated with the mobility inconsistency of that node and the spatial connection with the observed phenomenon [4]. Bursty traffic is more likely in a scenario with high mobility variations and low spatial links. Conversely, balanced traffic is more likely when mobility discrepancy decreases and spatial correlation upsurges. These observations point out that certain mobility characteristics can produce the desired outcome in different temporal constructions of network traffic. On the other hand, mobility-based WSNs are usually preferable over static WSNs because they result in better energy efficiency, enhanced coverage, improved object tracking, and higher channel capacity [5]. There are several WSN applications where nodes should be capable of adopting mobility, which require proper consideration [6]. The lack of mobility support also highly distracts the routing performance in WSNs. As a result, network topology changes unpredictably and paths frequently fail, which may increase packet delay and packet loss. Moreover, the QoS provisioning at the lower layers and the transport layer relatively correlates with the presence of mobility. Otherwise, sensor nodes experience the issues of emitting, increased latency, jitter and congestion. There are several mobility models available in the literature, all of which are particularly good candidates for ad-hoc WSNs, but their behavior in WSNs worsens QoS parameters and results in high energy consumption. For example, RWMM performs reasonably well in ad-hoc wireless networks, but is a poor candidate for WSNs due to weak choice of velocity distribution and uniform distribution [7; 8; 9]. To overcome the shortcomings of RWMM, the nomadic community mobility model (NCM) was introduced. This model is suitable for military applications and mobile communication in conferences because nodes move randomly as a group from one location to another. However, the reference point of each node is identified based on the overall movement of the group [10; 11]. This model consumes an excess energy when determining the location of a single node. To handle the mobility of sink nodes, CMM was introduced. This model captures data while following a circular pathway that is based on static points. A major shortcoming of this model is that nodes must remain motionless for eight or sixteen times in each cycle. In order to extend the network lifetime, WMM, based on eight directions, was introduced [12], but this model is specifically designed for sink nodes, but nodes have only group mobility support. Consequently, in determining the location of a single node, group nodes move and consume energy [13]. As a result, WMM mobility model suffers due to the extra pause time, the speed of nodes, and the dependency of nodes- movement in the group causes the network performance to slow down [14]. Furthermore, existing mobility models are fit for determining the sink mobility, but experience problems in the case of node mobility.