Data sharing in cloud computing happens with multiple participants to freely distribute the group data, which focuses on advancing the effectiveness of work in cooperative backgrounds and has attained widespread benefits. The main intent of this article is to accomplish a virtual machines (VMs) placement and migration model using a hybrid meta-heuristic concept. A new meta-heuristic algorithm named DJ-HA is developed for optimal VM placement and migration to reduce the count of active servers, and minimization of makespan, and energy consumption with a faster convergence rate in a cloud background. Then, the VM migration is done based on the multi-objective function concerning energy consumption and makespan using the same hybrid DJ-HA.From the result analysis, the energy consumption of the DJ-HA is correspondingly secured at 4.3%, 3.5%, 31%, and 33% more advanced than PSO, GWO, DHOA, and JA, at the 100th iteration for Experiment 1. Accordingly, the cost function of the suggested DJ-HA is secured at 88.8%, 89.4%, 33.3%, and 50% increased than PSO, GWO, DHOA, and JA at the 100th iteration for Experiment 4. Hence, it is proved that the suggested VM migration using DJ-HA is enriched than the other conventional algorithms.

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The emerging trends of wireless sensor network (WSN) are estimated to afford a wide range of applications, such as battlefield surveillance, environmental monitoring, and smart spaces and so on. The coverage problem is an essential concern in the WSN. In this paper seeks to address the problem of hole detection and healing in mobile WSNs. This paper discuss the main drawbacks of existing solutions and identify four key elements that are critical for ensuring effective coverage in mobile WSNs: (i) Identifying the boundary of Region of Interest, (ii) Finding the coverage holes and estimating their characteristics, (iii) Identifying the best target locations to relocate mobile nodes to repair holes, and (iv) Dispatching mobile nodes to the target locations while minimizing the moving and messaging cost. This paper proposes a lightweight and comprehensive solution called Holes detection and healing, that addresses all of the aforementioned aspects. HEAL is a distributed and localized algorithm that operates in two distinct phases. First, a collaborative mechanism, called Distributed Hole Detection (DHD), is proposed to identify the boundary nodes and discover holes. Second, this paper presents a virtual force- based hole healing algorithm. Unlike existing algorithms, HEAL algorithm relocates only the adequate nodes within the shortest times with the lowest cost. Simulation results shows that HEAL provide a cost-effective and an accurate solution.