# Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks
## 2 Related Work  
A lot of work has been done in maximizing the performance of the network via proposing different routing techniques. [PERSON] et al. introduce a distributed coverage hole repair algorithm (HORA) [14]. The proposed algorithm considers the movement of sensor nodes. Each node checks it status whether it is Cross Triangles (CT), Hidden Cross Triangles (HCT) or Non Cross Triangle (NCT) in order to minimize overlapping region. Neighbor node with highest overlapping region will move towards coverage hole to fill the gap. HORA helps to improve network lifetime and maximizes the throughput but its application in delay sensitive area degraded due to hole repairing process. Energy hole is one of the major factor which minimizes the network lifetime. Death of the nodes in the innermost region of the sink minimizes the network performance. A well known \"Load Balancing Technique\" (LBT) [15] aims to recover energy hole by adjusting the transmission power of sensor nodes. The proposed technique unable to highlight energy hole problem. [PERSON] et al. [16] alleviate energy hole through deployment of super nodes in the region close to the sink. The nodes near the sink turn on their scheduling power when all the data are gathered by super nodes on the boundary of the sink region. The scheme able to alleviate energy hole however the problem of void hole still exists which decreases the performance of the network. In order to control uneven energy consumption [PERSON] et al. [17] propose a ring model and define the per node traffic load and energy consumption. According to the observation, sensor nodes near the sink relay more traffic as compared to sensor nodes far from the sink. Based on their analysis sensor nodes in the region close to the sink has high energy consumption thus die out early which creates energy hole around the sink. A cluster based model \"Energy-efficient HOle Removing Mechanism\" (E-HORM) is presented by [PERSON] et al. [18] to overcome energy hole. In the propose scheme sleep scheduling mode is adopted for energy saving. Maximum distance nodes are selected for calculating the maximum energy for transmission of data. An energy threshold \"\(E_{th}\)\" is defined. If a node energy level falls below this \(E_{th}\), it cannot transmit data. The propose scheme able to maximize network lifetime and stability period in expense of delay. [PERSON] et al. [19] propose an \"Improved Hole Detection Healing and Replacing Algorithm for optimal coverage in Wireless Sensor Networks\" (IHDHRA) in order to maximize network lifetime via increasing the probability of packet loss. The propose algorithm uses nodes replacement strategy in order to avoid hole. High energy level node is selected for replacement such that the overall coverage is not disturbed. Maximum lifetime is achieved. However scalability issue and robustness decreases the performance. For energy balancing, an \"Energy Balance Mechanism\" (EBM) is proposed by [PERSON] et al. [20] to maximize the performance of the network. A corona based model is considered such that to balance the energy among the nodes. Required energy of every node is calculated based on its initial energy in respective corona and corona load. The proposed model aim to improve network lifetime. However extra energy is provided to these nodes which is not a best solution for lifetime maximization. [PERSON] et al. [21] propose an \" Energy-Efficient Data Sensing and Routing in unreliable energy-harvesting wireless Sensor network\" (EEDSRS) that performs both data sensing and data routing. EEDRS is performed in three steps. In first step an adaptive exponential weighted moving algorithm is proposed for estimation of link quality. Second, a distributed energy efficient rate allocation is performed for data sensing and routing for lifetime maximization through optimal data sensing rate. In last, data is routed through the links via energy efficient path. The algorithm aims to optimize the network performance but it is purely a MAC layer protocol which increases the complexity.