Towards Robust Fog/Edge Computing Infrastructure with Risk Adjusted Multi-Connectivity

Abstract

Emerging communication infrastructures, including Fog/Edge computing, are expected to carry users/applications with wide range of Quality of Service (QoS) requirements. For missioncritical applications, in addition to the expected performance, these requirements also include limitations on risk of the performance deterioration below certain level. Since risk mitigation is possible at the cost of either reduced expected performance or expenditure of additional resources, e.g., transmission power in wireless networks, efficient risk mitigation should consider these inherent tradeoffs. However, even evaluation of the corresponding tradeoffs in large-scale networks is a challenging problem, let alone efficient managing them. In this paper we suggest that diverse user risk tolerance levels can be incorporated into conventional network optimization frameworks by replacing user rate/throughput with the Entropic Rate at Risk (ERaR). We consider risk due to scenario-based uncertainty, where different scenarios include a "normal" scenario without jamming as well as feasible jamming scenarios. We demonstrate that ERaR user maximization results in user multi-connectivity to several Base Stations (BSs) when benefits of connectivity diversification out weight the "inefficiencies" due to connectivity to "distant" BSs. We propose an approximate solution to ERaR maximization for risk averse users, which is based on linear interpolation between the corresponding solutions for risk neutral and extremely risk averse users. Future work should incorporate this user risk adjusted optimization into the overall system optimization for users with diverse risk tolerance levels through risk pricing.