شیخ محمد یعقوب شرودي: حیاته، خدماته وآثارہ العلمیة

Hazrat Maulana Muhammad Yaqoob Sharrudi, also known as Sheikh Sharrudi; born 1930- 2007) was a religious saint, preacher, researcher, mystic and imam. In this research paper the works of Sheikh Sharrudi is elaborated in a sophisticated manner, His numerous works were written in Brohvi and Balochi and then translated into Urdu, Arabic, Pashtu and many other languages. He had not only worked for the renaissance of Islam but also propagated the “true Islam", He gave solutions for the weaknesses because of which Islam had suffered for hundreds of years. He opined that preaching of Islam (Dawat o Tableegh) was necessary for Islam, establishing Sharia and saving Islam from both; secularism and nationalism. Has publicly disclaimed sectarianism in Islam.

Resource Management and Energy Cooperation in Wireless Cellular Networks

Wireless communication has seen exponential growth in the past few decades due to advancements in digital communication technologies resulting in emerging wireless technologies such as LTE-A and WiMAX. Resultantly, wireless communication is becoming the main choice for voice as well as data communication. However, the increasing voice, data and internet services are costing heavy on resources. The consequent resource constraint is driving the technology developers to look for resource optimization solutions in all domains, particularly energy. The future radio access networks (RAN) like 5G will comprise denser and diverse heterogeneous networks (HetNets) of macro, micro, pico and femto BSs. Energy resource management of such networks is of prime concern besides improving throughput, latency and quality of service. This involves improving energy efficiency of all elements such as back haul network, data centers, base stations and mobile terminals. Amongst these, the base station is the most energy hungry entity, consuming as much as 60% of the networks energy. Research is, therefore, focusing component, system and network level energy efficiency improvements by employing schemes such as ''energy cooperation'' between base stations. The number of BS sites, worldwide, are expected to increase to more than 11 million, consuming 98 TWh annually, by year 2020. Consequently, it is resulting in increased GHG emissions since most of the power comes from the fossil fuel based energy sources. Thus, BSs have become a strong candidate for different energy efficient techniques as well as incorporation of renewable energy sources (RES) such as solar panels and wind turbines. Base stations are ideally suited to have renewable sources installed because all four elements of energy generation, transmission, storage and consumption are located at one place. RES are not only feasible for stand-alone or off-grid BS, but also for on-grid BS, especially smart-grid tied. Equipping base stations with renewable energy sources of solar and wind is feasible for areas having good sunshine and windy conditions. By considering the fluctuations xi in the base station load because temporal and spatial variations in traffic, it is possible to have energy cooperation between nodes. A base station having deficient green (harvested) energy is encouraged to borrow it from a neighbor rather than acquire it from GHG emitting sources such as diesel generator. A novel extension of this scheme is designed to combine it with sleep mechanism in networks where lean base stations are put to sleep and their energy and load are distributed in the network. The strategies of energy resource optimization thus incorporated yield positive results in energy cost savings for the network. In this research, initially, a PV array of 7.8 kW and a wind turbine of 7.5 kW peak power has been modeled for Islamabad region, for a BS consuming 2.35 kWh peak energy. It is shown that base stations harvesting renewable energy may have surplus energy that can be shared with other base stations or even sold back to the grid through net metering. Since the energy consumption of a BS is not fixed and fluctuates with the traffic load, the energy produced from renewable energy sources may be more than the energy consumed, especially during off peak hours, opening the venues for energy cooperation between nodes. We consider a cellular network of N macro BSs equipped with energy harvesting systems (solar, wind or both) modeled for site whose weather parameters are known. The network is powered by the conventional grid (Utility), with a diesel generator providing backup power at each BS. We consider a finite horizon time slotted system where the decision to share energy is made for a definite time t (1 ≤ t ≤ T). The key elements of our system model are; solar/wind energy harvesting base stations, a battery bank for energy storage at the base station, inter-connectivity between the base station through grid, smart grid or central controller, for energy transfer, and an energy management unit at the base station running the algorithms. We propose a frame work for traffic aware sustainable and environmental friendly base station operation through energy cooperation (TASEEC) in grid connected green cellular network, where each base station is encouraged to acquire energy from renewable source and all base stations are also connected to the utility grid. The mathematically modeled framework jointly takes care of static and traffic aware load on the BS. In TASEEC, the optimizer always selects economical power source for buying purposes. The frame-work is based on the fact that the base station operators have an agreement on energy cooperation and on cooperation tariff. The main aim is to jointly minimize the operational cost and greenhouse gas emissions. The cost xii includes self-generation cost, cost of energy purchased from other BSs and cost of energy procured from grid. The non-linear problem is linearized by applying McCormick approximation and solved through interior point method. The framework is further extended to a heterogeneous umbrella network with base station on/off switching incorporated in addition to energy cooperation scheme discussed above. The results are shown for individual base stations and the energy cost savings -as a result of proposed energy cooperation strategy - are depicted as a percentage reduction in network’s energy consumption cost.