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New communication protocols, as WiFi Direct, are now available to enable efficient Device-to-Device (D2D) communications in wireless networks based on portable devices. At the same time, new network paradigms, as Content-Centric-Networking (CCN), allow a communication focused on the content and not its location within the network, enabling a flexible location for the content, which can be cached in the nodes across the network. In such context, we consider a multi-hop wireless network adopting CCN-like cooperative caching, in which each user terminal acts also as a caching node. We propose an interestbased insertion policy for the caching, based on the concept of "social-distance" borrowed by online recommendation systems, to improve the performance of the overall network of caches; the main idea is to store only the contents which appear to be of interest for the local user. We show that our proposed scheme outperforms other well-known insertion policies, that are oblivious of such social-distance, in terms of cache hit probability and access delays.

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Nowadays, the continuously increasing demand for high data traffic and providing different quality of services (QoS) to the customer are very challenging tasks for all network operators. In the last few years, mobile data traffic is increased to a significant extent and half of the traffic is provided through WiFi technology which is known as WiFi offloading. To overcome the increasing traffic demand, WiFi offloading is the best option to reduce the burden of cellular networks. So, by aggregating existing indoor WiFi technology to the cellular network increases the network capacity and provides better QoS to customers. In this article, we propose and implement the LTE-WiFi aggregation system where eNodeB is responsible for the aggregation of the WiFi access point without modifying the core network. Furthermore, the proposed system is integrated with the mobile-CORD (M-CORD) platform which leverages software defined networking (SDN), network function virtualization (NFV), and cloud technologies for providing a 5G environment. M-CORD platform has three main modules: service orchestrator (XOS), SDN controller ONOS, and OpenStack. One of the important features of M-CORD is to provide virtualized core network functions that enable the users to automatically customize, monitor, and control the resources of the network. Due to ONOS controller support, we can easily scale up the network instances by giving the configurations to service orchestrator XOS of the M-CORD. The implementation of the proposed system is based on the OpenAirInterface (OAI) platform which provides open sources implementation of core and access networks. The aggregation of both LTE and WiFi technologies is done at the PDCP layer in a very tight coupling way. Moreover, we test our proposed system with three kinds of policies for UDP and TCP traffic: LTE only, WiFi only, and LTE-WiFi aggregated. The experimental results show that our proposed LTE-WiFi aggregated system gives better performance and provides high bandwidth as compared to the LTE network.

The ongoing load-shedding and energy crises due to mismanagement of energy produced by different sources in Pakistan and increasing dependency on those sources which produce energy using expensive fuels have contributed to rise in load shedding and price of energy per kilo watt hour. In this paper, we have presented the linear programming model of 95 energy production systems in Pakistan. An improved multiverse optimizer is implemented to generate a dataset of 100000 different solutions, which are suggesting to fulfill the overall demand of energy in the country ranging from 9587 MW to 27208 MW. We found that, if some of the power-generating systems are down due to some technical problems, still we can get our demand by following another solution from the dataset, which is partially utilizing the particular faulty power system. According to different case studies, taken in the present study, based on the reports about the electricity short falls been published in news from time to time, we have presented our solutions, respectively, for each case. It is interesting to note that it is easy to reduce the load shedding in the country, by following the solutions presented in our dataset. Graphical analysis is presented to further elaborate our findings. By comparing our results with state-of-the-art algorithms, it is interesting to note that an improved multiverse optimizer is better in getting solutions with lower power generation costs.