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There is emerging trend in power system, i.e., energy internet that provides energy production, transmission, storage and utilization. Which is used to manage and control energy centrally by using information and communication technologies. In this paper, coordinated management of renewable and traditional energy is focused. In proposed work, storage system is embedded with renewable resources in microgrid, so that after satisfying users energy requirement, surplus energy can be stored in battery. Energy management is performed with storage capacity includes cost of renewable resources, depreciation cost of battery and bidirectional energy transmission. User and microgrid are two players that are involved in non cooperative game theory. In order to maximize the payoff of user as well as microgrid, the two stage non cooperative game theoretic method optimizes battery capacity and prices. Which are charged by micro grid from user and optimize user energy consumption. The distributed algorithm is proposed to explain nash equilibrium which ensures Pareto optimality in terms of increasing pay off of both stakeholder. Furthermore, forecasting algorithm back propagation (BP), Support Vector Machine (SVM) and Stacked Auto Encoder (SAE) are used for forecasting historical data related to solar power generation. Predicted data is, thus used by microgrid in defining energy prices and battery storage capacity.

Numerous fields have wide range of applications regarding Internet of Things (IoT) specially smart cities. Due to increasing day to day growth in number of applications, there is exponential rise in requirement of IoT devices. IoT network is becoming complex persistently which brings the significant challenge to the robustness of network topology. IoT is the backbone of smart cities due to inter connecting wide range of devices and converting a conventional city to smart city. To improve network topology robustness against targeted, malicious and intentional attacks have become a critical issue. To deal with the problem in this article, Enhanced Angle Sum Operation (EASO) ROSE is presented. Proposed scheme improves the robustness of network topology without effecting node degree distribution and scale-free property. Topology robustness is achieved by degree difference and angle sum operations. Extensive simulation results verify that our proposed scheme efficiently generate scale-free typologies for IoT in smart cities and significantly improve topology robustness against malicious and targeted attacks.

Number of wireless sensing device protocols have been introduced in last decade due to enhancement in automation of battle field and other commercial applications. Main focus was to improve power efficiency and life span of the network to ensure smooth communication across the network. Protocols for heterogeneous networks have been mainly working on power level quantization. TBEENISH protocol will improve threshold criteria to elect cluster head for improving life span as well as it will also present complete visibility of sensing device. Life time of complete network which has never been shown by researchers previously. Which helps to devise more effective protocols to decrease latency and increase fault tolerance.