No abstract

In SDN, forwarding devices can only operate correctly while connected to a logically centralized controller. To avoid single-point-of-failure, controller architectures are usually implemented as distributed systems. In this context, recent literature identified fundamental issues, such as device isolation and controller overload, and proposed controller placement strategies to tackle them. However, current proposals have crucial limitations: (i) device-controller connectivity is modeled using single paths, yet in practice multiple concurrent connections may occur; (ii) peaks in the arrival of new flows are only handled on-demand, assuming that the network itself can sustain high request rates; and (iii) failover mechanisms require predefined information, which, in turn, has been overlooked. This paper proposes Survivor, a controller placement strategy that addresses these challenges. The strategy explicitly considers path diversity, capacity, and failover mechanisms at network design. Comparisons to the state-of-the-art on survivable controller placement show that Survivor is superior because (a) path diversity increases the survivability significantly; and (b) capacity-awareness is essential to handle overload during both normal and failover states.

In many aspects of human activity, there has been a continuous struggle between the forces of centralization and decentralization. Computing exhibits the same phenomenon; we have gone from mainframes to PCs and local networks in the past, and over the last decade we have seen a centralization and consolidation of services and applications in data centers and clouds. We position that a new shift is necessary. Technological advances such as powerful dedicated connection boxes deployed in most homes, high capacity mobile end-user devices and powerful wireless networks, along with growing user concerns about trust, privacy, and autonomy requires taking the control of computing applications, data, and services away from some central nodes (the "core") to the other logical extreme (the "edge") of the Internet. We also position that this development can help blurring the boundary between man and machine, and embrace social computing in which humans are part of the computation and decision making loop, resulting in a human-centered system design. We refer to this vision of human-centered edge-device based computing as Edge-centric Computing. We elaborate in this position paper on this vision and present the research challenges associated with its implementation.