Rana Liaqat Ali

Federated cloud resource management

Federation of clouds is the future of cloud computing, mobile cloud computing, Internet of things, and big data applications. The utilization of federated resources is envisioned to increase the quality of service, cost benefits, and reliability. Resource management in the federation of multiple clouds is a pressing issue owing to the lack of cross-domain knowledge, security, trust, and administrative policies. This study classifies these resource management functions in the federated cloud environment into resource pricing, resource discovery, resource selection, resource monitoring, resource allocation, and disaster management. Each federated resource management function is discussed, and insights into state-of-the-art research are then provided. These resource management functions are also compared based on the performance metrics that are suitable for an individual function. Finally, we indicate the open challenges for further research with regard to each classified resource management function.

Design and Implementation of Smart Billing and Automated Meter Reading System for Utility Gas

Billing automation systems for public utilities (e.g. electricity, gas and water) have been widely studied and implemented in developed countries across the world. But in Pakistan, this technology is still on its way to be implemented for domestic as well as for industrial consumers. This paper explores the design, implementation and application of billing automation system for gas consumers in Pakistan. For low gas consumption (domestic consumers), a prepaid meter has been designed which needs a prepaid card to keep the gas supply continue. Similarly for high gas consumption (industrial consumers), the gas meter is wirelessly connected with the regional billing office. In this way the billing office is able to directly communicate with the meter and records its gas consumption reading. Along with the gas, this system can easily be enhanced to measure the consumption of electricity and water.

A Robust Least Mean Square Algorithm for Adaptive Array Signal Processing

Least Mean Square (LMS) has been the most popular scheme in the realization of adaptive beamforming algorithms. In this paper a Robust Least Mean Square (R-LMS) algorithm is proposed which uses ratio parameters to control the contribution of product vectors in the weight upgrading process. The idea behind the proposed scheme is inclusion of previous information in place of relying solely on current sample. The performance enhancement by R-LMS algorithm is achieved with insignificant increase in computational complexity of LMS algorithm, so the crux of the conventional technique is not lost. Simulation results are also presented which illustrate that R-LMS provides relatively fast convergence, less Brownian motion and improved stability.

Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results.

A compact microstrip patch antenna with circular snipped slot for GSM, Wi-Fi and WiMAX applications

A rectangular microstrip patch antenna with probe feed is proposed in this paper. The patch of an antenna has a key circular slot which is auxiliary truncated in circular style resulting three narrow bands of the most worthy and in-use wireless technologies of the modern age, that are GSM, Wi-Fi and WiMAX. The resonating bandwidths of the presented antenna ranges from 1.79 to 1.83 GHz for GSM 1800, 2.40 to 2.48 GHz for Wi-Fi and from 3.32 to 3.42 GHz used for WiMAX. The design process has been carried out in HFSS (High Frequency Structure Simulator) and antenna is fabricated manually, to assess and evaluate the real characteristics.

Ground plane tunable printed monopole antenna for wireless communications

A compact printed monopole antenna with tunable ground for adjustment of bandwidth is proposed. The achieved bandwidth is regulated by the length of ground plane. Presented antenna has five slits in its rectangular patch controlling the bandwidth and the frequency shifts. The simulated results are obtained using HFSS (High Frequency Structure Simulator). FR4 substrate of 30×24×1.6 mm3 is used for the fabrication. The measured results of prototype are acquired by network analyzer and anechoic chamber. The offered antenna is applicable for GSM (1800, 1900), UWB, UMTS (1900, 2100), Wi-Fi, WiMAX, Zig-bee, and Satellite Communication applications.

Automated Frequency Distribution, Management & Assignment (AFDMA) in IEEE 802.16

Frequency is amongst the most exclusive and most costly resources in wireless communication networks, especially, while considering the demands of Broadband Wireless Access (BWA). In BWA, the management of frequency distribution and its effective utilization is of utmost importance. This research explores possible ways to ensure the most effective allocation of bandwidth resources and their best possible utilization on need basis. The model for static frequency allocation has been optimized and the dynamic frequency management has been calculated while dividing the users in different user classes on the basis of their needs and requirements. The effect of ping-pong handovers has been handled by introducing an inter-base station handshake process, allowing effective management of fast moving users. Automated Frequency Distribution, Management and Assignment (AFDMA) provides maximum bandwidth optimization in order to ensure increased network performance and Quality of Service (QoS).