With the passage of time, the data is growing exponentially and the mostly endured areas are social media networks, media hosting applications, and servers. They have thousands of Tera-bytes of data and the efficient systems, however, they are as yet confronting issue to oversee such volume of information and its size is growing each day. Data systems retrieve information with less time of In-memory. Instead of each factor data systems are required to define good usage of cache and fast memory access with help of optimization. The proposed technique to solve this problem can be the optimal indexing technique with better and efficient utilization of Cache and having less overhead of DRAM with the goal that energy can also be saved for the high-end servers.

Internet of Things (IoT) systems has become a global trend enhancing the capabilities smart computing era involving a variety of distributed end-devices and multi-scalable applications. The collaborative nature of IoT systems connected through the Internet increases the heterogeneity of coming data streams that need to be processed for correct decision making in a real-time environment. The processing of huge data streams for remotely distributed IoT systems create loops for data breaches and open new challenges for security and scalability of system testing. Thus, the testing of IoT systems is becoming the necessity, requires automated testing framework due to the amount of IoT devices and processing of data events is prone to error by traditional software testing. An automated IoT testing service based framework is purposed in this paper, to test the distributed IoT systems by reducing cost and scalability issues of software testing. The infrastructure of IoT systems demands a large number of platforms be developed which requires systematic testing approach. Therefore, the purposed automated IoT testing as a service model performs distributed interoperability testing, oneM2M based conformance testing, security testing of distributed systems and validating semantics/syntactic testing of IoT devices in a systematic approach. Lastly, to provide more strength to the work we discussed and analyze existing IoT testing models to evaluate our proposed model.

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