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Localization is one of the key applications of visible light communication (VLC) using which sub-centimeter level positioning accuracy is possible. Many visible light-based positioning (VLP) systems have been designed by industry and the research community. Their commercial viability is hampered by the requirement of significant changes in the deployed lighting infrastructure, resulting in a prohibitive increase in the cost and overhead of deployment. In this paper, we review passive VLP systems an emerging paradigm that offers hope to overcome this challenge and thus can catalyze commercial adoption of a new wave of VLP systems. Unlike active systems, passive ones provide unprecedented flexibility and can enable new potential applications and scenarios such as ability to track users not carrying photosensors. Both natural light sources e.g., sunlight and artificial man-made sources can be used to transmit location information. This paper provides a taxonomy of recently proposed passive VLP systems which is supported by several examples from the recent research literature. A comparative performance of these systems based on factors like accuracy and infrastructure changes is provided along with their limitations.

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Cloud computing is one of the latest and upcoming paradigm that offers huge benefits such as reduced time to market, unlimited computing power and flexible computing capabilities. It is a model that provides an on-demand network access to a shared pool of computing resources It comprises a large number of concepts primarily Load Balancing, Scheduling, etc. This paper discusses load balancing as a mechanism to distribute the workload evenly to all nodes in the system to achieve a higher resource utilization and user satisfaction. It helps in allocation and de-allocation of instances of applications without   failure. This paper reports a new load balancing technique using modified credit based system using task length, task priority and its cost. The proposed algorithm has been implemented in cloudsim toolkit and its comparison with existing algorithm has been discussed in the paper.

In present days cloud computing is one of the greatest platform which provides storage of data in very lower cost and available for all time over the internet.But it has more critical issue like security, load management and fault tolerance. In this paper we are discussing Load Balancing approach. Many types of load concern with cloud like memory load, CPU load and network load. Load balancing is the process of distributing load over the different nodes which provides good resource utilization when nodes are overloaded with job. Load balancing has to handle the load when one node is overloaded. When node is overloaded at that time load is distributed over the other ideal nodes. Many algorithms are available for load balancing like Static load balancing and Dynamic load balancing.

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