This paper presents an instance based approach to diagnosing failures in computing systems. Owing to the fact that a large portion of occurred failures are repeated ones, our method takes advantage of past experiences by storing historical failures in a database and retrieving similar instances in the occurrence of failure. We extract the system `invariants' by modeling consistent dependencies between system attributes during the operation, and construct a network graph based on the learned invariants. When a failure happens, the status of invariants network, i.e., whether each invariant link is broken or not, provides a view of failure characteristics. We use a high dimensional binary vector to store those failure evidences, and develop a novel algorithm to efficiently retrieve failure signatures from the database. Experimental results in a web based system have demonstrated the effectiveness of our method in diagnosing the injected failures.

Abstract — We present Sieve – an infrastructure for fast content-based data distribution to interested users. The ability of Sieve to filter and forward high-bandwidth data streams stems from its distributed pipelined architecture. The complex message filtering task is broken-up into a sequence of light-weight filtering components resulting in high end-to-end throughput. Furthermore, since each component is assigned to a node based on its resource constraints, the queue buildup inside the nodes is minimal resulting in low end-to-end latency. Our experimental results based on real system implementation show that Sieve can sustain a throughput of more than 5000 messages per second for 100000 subscriptions with predicates of 10 attributes. Index Terms — Content-based Information Dissemination, Publish-Subscribe System, Event Stream Filtering

We present SPIDER-a system for fast replication or distribution of large content from a single source to multiple sites interconnected over Internet or via a private network. In order to exploit spatial diversity of the underlying network, SPIDER uses an overlay structure composed of dedicated transit nodes (TNs). The data transport mechanism in SPIDER leverages this overlay structure to provide a coordinated approach that minimizes the maximum time to replicate to all destination sites (the make span of content replication). In order to achieve this objective, SPIDER employs two orthogonal components: a) creation of multiple dynamic distribution trees using the transit nodes b) end-to-end reliable data transport with flow control on these trees by chaining point-to-point TCPs. We further present simulations based results to quantify benefits of tree construction algorithms in random topologies. We evaluate the real implementation of the SPIDER in Planet Lab and observe a 2-6 times speed up compared to different existing schemes.

In this paper, we present the design and implementation of Smart Messages, a distributed computing platform for networks of embedded systems based on execution migration. A Smart Message (SM) is a user-defined distributed program which executes on nodes of interest, named by their properties, and uses an explicit lightweight migration to reach these nodes. During migrations, an SM carries its code and execution state, and it self-routes at each intermediate node between two nodes of interest. The nodes in the network cooperate to support the SM execution by providing a virtual machine and a shared memory region addressable by names (tag space). To illustrate the flexibility of SMs to program real world applications, we describe EZCab, an application for booking cabs in densely populated urban areas. We also present experimental results to quantify the performance achieved by the SM prototype.

Smart messages (SMs) are dynamic collections of code and data that migrate to nodes of interest in the network and execute on these nodes. A key challenge in programming pervasive computing environments using SMs is the ability to route SMs to nodes named by content. This paper describes the SM self-routing mechanism, which allows SMs to route themselves at each hop in the path toward a node of interest. SM applications can choose among multiple content based routing algorithms, switch dynamically the routing algorithm in use, or even implement the best suited routing algorithm for their needs. The main benefits provided by self-routing are high flexibility and resilience to adverse network conditions. To demonstrate these benefits, we present proof-of-concept implementation, simulation results, and analysis for the SM self-routing mechanism using several content-based routing algorithms. We also show preliminary results for SM routing algorithms executed over our SM prototype implementation.

The next generation of computing systems will be embedded, in a virtually unbounded number, and dynamically connected. The current software, network architectures, and their associated programming models are not suitable for this scenario. This paper presents a distributed computing model, Cooperative Computing, and the Smart Messages architecture for programming large networks of embedded systems. In Cooperative Computing, distributed applications are dynamic collections of migratory execution units, called Smart Messages, working to achieve a common goal. Virtually any user-defined distributed application can be implemented using our model. We present preliminary results for our prototype implementation as well as simulation results for two previously proposed applications for sensor networks, Directed Diffusion and SPIN, implemented using Smart Messages.