We present VCD, a novel system for enabling high-bandwidth content distribution in vehicular networks. In VCD, a vehicle opportunistically communicates with nearby access points (APs) to download the content of interest. To fully take advantage of such transient contact with APs, we proactively push content to the APs that the vehicles will likely visit in the near future. In this way, vehicles can enjoy the full wireless capacity instead of being bottle-necked by the Internet connectivity, which is either slow or even unavailable. We develop a new algorithm for predicting the APs that will soon be visited by the vehicles. We then develop a replication scheme that leverages the synergy among (i) Internet connectivity (which is persistent but has limited coverage and low bandwidth), (ii) local wireless connectivity (which has high bandwidth but transient duration), (iii) vehicular relay connectivity (which has high bandwidth but high delay), and (iv) mesh connectivity among APs (which has high bandwidth but low coverage). We demonstrate the effectiveness of VCD system using trace-driven simulation and Emulab emulation based on real taxi traces. We further deploy VCD in two vehicular networks: one using 802.11b and the other using 802.11n, to demonstrate its effectiveness.

Disruption tolerant networks (DTNs) are a class of networks in which no contemporaneous path may exist between the source and destination at a given time. In such a network, routing takes place with the help of relay nodes and in a store-and-forward fashion. If the nodes in a DTN are controlled by rational entities, such as people or organizations, the nodes can be expected to behave selfishly and attempt to maximize their utilities and conserve their resources. Since routing is an inherently cooperative activity, system operation will be critically impaired unless cooperation is somehow incentivized. The lack of end-to-end paths, high variation in network conditions, and long feedback delay in DTNs imply that existing solutions for mobile ad-hoc networks do not apply to DTNs. In this paper, we propose the use of pair-wise tit-for-tat (TFT) as a simple, robust and practical incentive mechanism for DTNs. Existing TFT mechanisms often face bootstrapping problems or suffer from exploitation. We propose a TFT mechanism that incorporates generosity and contrition to address these issues. We then develop an incentive-aware routing protocol that allows selfish nodes to maximize their own performance while conforming to TFT constraints. For comparison, we also develop techniques to optimize the system-wide performance when all nodes are cooperative. Using both synthetic and real DTN traces, we show that without an incentive mechanism, the delivery ratio among selfish nodes can be as low as 20% as what is achieved under full cooperation; in contrast, with TFT as a basis of cooperation among selfish nodes, the delivery ratio increases to 60% or higher as under full cooperation. We also address the practical challenges involved in implementing the TFT mechanism. To our knowledge, this is the first practical incentive-aware routing scheme for DTNs.

Sophisticated middlebox services-such as network monitoring and intrusion detection, DDoS mitigation, worm scanning, XML parsing and protocol transformation-are becoming increasingly popular in today's Internet. To support high- throughput, these services are often deployed on distributed memory, multi-processor (DM-MP) hardware platforms such as a cluster of network processors. Scaling the throughput of such platforms, however, is challenging because of the difficulties and overheads of accessing persistent, shared state maintained by the services. In this paper, we describe the design and implementation of Oboe, a run-time system for DM-MP platforms that addresses the above challenge through two foundations: (1) category-specific management of shared state, and (2) adaptive flow- level load distribution for addressing persistent processor overload. Our simulations demonstrate that Oboe can achieve performance within 0-5% of an ideal adaptive system. Our prototype implementation of Oboe on a cluster of IXP2400 network processors, demonstrates the scalability achieved with increasing number of processors, number of flows and state size.

In this paper, we describe the design and evaluation of a scheduler (referred to as Everest) for allocating processors to services in high performance, multi-service routers. A scheduler for such routers is required to maximize the number of packets processed within a given delay tolerance, while isolating the performance of services from each other. The design of such a scheduler is novel and challenging because of three domain-specific characteristics: (1) difficult-to-predict and high packet arrival rates, (2) small delay tolerances of packets, and (3) significant overheads for switching allocation of processors from one service to another. These characteristics require that the scheduler be agile and wary simultaneously. Whereas agility enables the scheduler to react quickly to fluctuations in packet arrival rates, wariness prevents the scheduler from wasting computational resources in unnecessary context switches. We demonstrate that by balancing agility and wariness, Everest, as compared to conventional schedulers, reduces by more than an order of magnitude the average delay and the percentage of packets that experience delays greater than their tolerance. We describe a prototype implementation of Everest on Intel's IXP2400 network processor