PurposeThis study aims to investigate the interplay between renewable energy development, unemployment and GDP growth within Bangladesh, India, Pakistan and Sri Lanka. The research underscores the significant role of renewable energy plays in stimulating economic growth and mitigating unemployment, offering crucial policy insights for sustainable growth in South Asia.Design/methodology/approachUtilizing the autoregressive distributive lag (ARDL) framework and Toda Yamamoto causality through the vector autoregressive (VAR) approach, the study analyzes the long-term and short-term impacts of these variables from 1990 to 2019.FindingsThis study reveals a significant co-integration among renewable energy consumption, unemployment and GDP growth in selected South Asian countries. The long-term estimation shows renewable energy consumption influences negatively economic progression in Bangladesh, with no notable correlation with unemployment. In contrast, Sri Lanka demonstrates an optimal relationship among all the variables. Short-run assessments reveal a significant positive relationship between renewable energy consumption and economic growth in India, while an inverse relationship is evident in Pakistan. Moreover, the relationship between unemployment and economic progression, the result shows a negative and significant relationship in India and Sri Lanka.Research limitations/implicationsThe study emphasizes the need for policy development concerning renewable energy development, unemployment reduction and sustainable economic growth in South Asia. While limitations exist, future research can expand upon this work by incorporating varied data, additional countries or alternative modeling techniques.Originality/valueThis research offers a unique exploration into the multidimensional impacts of renewable energy consumption, unemployment and economic growth in the South Asian context, an area previously unexplored in such depth.

Simulation of wireless networks has recently drawn considerable attention in the area of abstraction. Simulation is a precious tool used to model complex systems where the desired network size is large in scale. For large mobile ad hoc networks, the most computation intensive tasks in simulation are computing interference and determining which receivers are in range of a transmitter. In both cases, O(N2) physical layer calculations are required for a wireless system of N nodes, which scales poorly. In this paper, a geometric model, minimal rectangular coverage area is devised for the optimization of the complexity of interference computations in simulations of wireless mobile ad hoc networks. This method lessens the number of unaffected nodes by considering less area as affected by transmission range, which exists outside the transmission range of a transmitter. However, the experimental results suggest that this geometric model reduce the affected coverage area 12.5% - 78.15% than existing grid based algorithm used in current version of NS2. This paper also discusses about the efficiency considerations of the algorithm in detail.

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