Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

EDCSuS: Sustainable Edge Data Centers as a Service in SDN-enabled Vehicular Environment

Abstract: Cloud computing has emerged as a popular technologies which provide on-demand services to the end users. Such services are hosted by massive geo-distributed data centers(DCs). Nowadays, connected vehicles in a smart city can also avail cloud services through Internet using cellular technologies. But, the advent of 5G technology has posed challenges for DCs such as-low latency and higher data rate requirements. To handle these challenges, edge-DCs(EDCs) can be deployed across a smart city to provide low latency services to the connected vehicles. In lieu of this, in this paper, EDCSuS: Sustainable EDC as a service framework in software defined vehicular environment is proposed. In EDCSuS, firstly, a software defined controller handles the incoming requests and suggest an optimal flow path. Secondly, a multi-leader multi-follower Stackelberg game is presented for resource allocation. Thirdly, to improve the resource utilization, a cooperative resource sharing scheme is designed, thereby minimizing the energy consumption of servers in the EDCs. Lastly, a caching scheme is presented to avert excessive energy consumption for retracing the lost link due to vehicular mobility. The efficacy of the proposed scheme has been evaluated using extensive simulations with respect to various parameters. The results obtained prove the effectiveness of EDCSuS.

An efficient localization approach to locate sensor nodes in 3D wireless sensor networks using adaptive flower pollination algorithm

Abstract: Localization in wireless sensor networks (WSNs) is required to examine the coordinates of the sensor nodes deployed in the sensing field. It is the process that determines the location of the target nodes relative to the location of deployed anchor nodes. The anchor nodes positions are known as the nodes that have GPS unit incorporated with them. All sensor nodes are generally not configured with GPS as it is not suitable for indoor environments and/or underwater areas. A network becomes more expensive and utilizes more energy if all nodes are equipped with GPS that is a major drawback of WSNs. Various localization schemes have been proposed in literature, while most research proposals deal with the study of 2D applications. However, in the 3D applications, the area under observation may have a complexity in the sensing environment. An optimized algorithm is required for the determination of node location in 3D environment. In this paper, we propose an adaptive flower pollination algorithm (AFPA) with enhanced exploration and exploitation capabilities of conventional FPA for the localization of sensor nodes in WSN. To test the performance of AFPA, benchmark functions (CEC 2019) are used to compare it with other meta-heuristics. The results show that proposed AFPA outperforms in terms of convergence speed and provides better results for most of the benchmark functions. Also, the proposed AFPA is tested on WSN Localization problem, it provides least localization error in comparison to other techniques applied in 3D WSN environments.

A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation

Abstract: Retinal blood vessels have been presented to contribute confirmation with regard to tortuosity, branching angles, or change in diameter as a result of ophthalmic disease. Although many enhancement filters are extensively utilized, the Jerman filter responds quite effectively at vessels, edges, and bifurcations and improves the visualization of structures. In contrast, curvelet transform is specifically designed to associate scale with orientation and can be used to recover from noisy data by curvelet shrinkage. This paper describes a method to improve the performance of curvelet transform further. A distinctive fusion of curvelet transform and the Jerman filter is presented for retinal blood vessel segmentation. Mean-C thresholding is employed for the segmentation purpose. The suggested method achieves average accuracies of 0.9600 and 0.9559 for DRIVE and CHASE_DB1, respectively. Simulation results establish a better performance and faster implementation of the suggested scheme in comparison with similar approaches seen in the literature.

Renewable Energy Management in Multi-microgrid Under Deregulated Environment of Power Sector

Abstract: Microgrid (MG) is the combination of different distributed generation units and local loads. It is a small self-sustaining power network which serves its local load. Generally it can be operated in grid connected mode or grid isolated mode. The objective of this paper is to maximize the social welfare and minimize operating cost. Social welfare/benefit with the operator may be used for giving subsidies to renewable based plant, farmers, society welfare, etc. This paper proposes an approach to maximize the social welfare of each microgrid through discriminated price auction mechanism. MATLAB Interior Point Solver (MIPS) method has been used for computing the corresponding allocations and price of each unit in the multi-microgrid system. Also, a comparison of social benefit and the operating cost of each microgrid considering both presence and absence of renewable energy sources is carried out. For analysis of this approach 49 bus system is used, which is divided as microgrid A (14 bus system), microgrid B (15 bus system), microgrid C (14 bus system) and rest of the buses are used in the main grid architecture and its dispatchable load buses. The results of this proposed method show that social welfare is maximized while optimally managing renewable-based distributed units with their conventional fuel based distributed generation units.

Design of a wearable MIMO antenna deployed with an inverted U-shaped ground stub for diversity performance enhancement

Abstract: A compact multiple input multiple output (MIMO) antenna operating at 2.45 GHz industrial scientific and medical band is presented for wearable devices. Open-end slotting is used to miniaturize the antenna dimensions. Inverted U-shaped ground stub is incorporated to reduce mutual coupling. On-body performance is analyzed on a three-layered equivalent tissue phantom model. The wide bandwidth of 300 MHz and port isolation of 30 dB are obtained from measured results. The antenna shows the efficiency of 40% and directivity of 4.56 dBi when placed at a gap of “s” = 4 mm from the body. Broadside radiation pattern and low specific absorption rate make the antenna suitable for on-body communication. Further, diversity performance is measured in terms of envelope correlation coefficient (ECC), diversity gain (DG), and channel capacity loss (CCL). The value of ECC is 0.025, DG is 9.98 dB, and CCL is 0.12 bits/s/Hz at 2.45 GHz. Antenna robustness is examined by bending the structure at different radii along the x-axis and y-axis. Performance of the proposed structure is reliable with structural deformation.