Abstract-Recently, there has been a surging interest on anonymizer technologies as a result of increasing privacy concerns and raising censorship barriers around the world. Tor network has emerged as the most popular option in avail thanks to its large volunteer base. However, popularity of Tor network is under threat of growing user frustration over low throughput and long latencies. Coincidentally multi-path routing proposals have become popular in tackling the similar performance issues in various contexts from data center networks to inter-domain routing. In this work, we apply multi-path techniques so as to overcome limitations in Tor's path construction and rigid congestion avoidance mechanisms which are major factors behind the unsatisfactory user experience. It turns out that multipath mechanisms nicely complement underlying onion-routing mechanisms of Tor via exploiting diversity in Tor network. Our preliminary evaluation on live Tor network revealed the significant potential of performance improvements achieved by multi-path techniques especially in increasing throughput which can offer up to 4 times speed up in data transmission durations. Also, multi-path mechanisms may increase reliability of the overall system against congestion or service-interruption based attacks in return of acceptable anonymity trade-offs. Besides these very promising features, application of multi-path techniques on anonymized routing introduces many open research questions calling for further research on data splitting, path construction, latency estimation techniques whose findings can benefit many research areas.

We propose a new architectural approach, CloudAssisted Routing (CAR), that leverages high computation and memory power of cloud services for easing complex routing functions such as forwarding and flow level policy management. We aim to mitigate the increasing routing complexity to the cloud and to seek an answer to the following question: "Can techniques leveraging the memory and computation resources of the cloud remedy the routing scalability issues?" The key contribution of our work is to outline a framework on how to integrate cloud computing with routers and define operational regions where such integration is beneficial.

Abstract-Today various highly-efficient protocols exist as wellknown solutions to a wide-range of routing problems. However, there exist a large variety of scenarios where routing protocols do not perform well due to peculiar nature of these routing problems (e.g. dynamism of highly mobile ad-hoc networks, large scale of social, p2p networks, QoS-aware Inter-domain routing). These routing problems can be drawn from various research areas like wireless networks, social networks, and even Physics through fluid dynamics. In this work, we analyze opportunistic path-vector protocols as a solution to some of these mentioned problems. Our approach is to redefine routing problem as a set of smaller scale problems which can be solved locally without requiring a global coordination but local communication. We also provide guidelines on how to solve these redefinedlocalized routing problems efficiently. Our analysis show that our method provide a good compromise between scalability and opportunity through smartly randomized (non-deterministic) choices. Although we analyze this tradeoff for specific cases in this work, a wider range of routing problems can be actually targeted through transformation methods with reasonable-costs.

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