666073
A Feasible Baseline Architecture for Building and Evaluating Distributed Systems
Although distributed networks and systems are widely deployed, an effective overall benchmark architecture is still lacking. Recently we defined and studied the fat-stack network architecture and found that it is both efficient and scalable to distributed systems of various scales. In precedent work, we theoretically proved that the fat-stack is universal by measure of routing efficiency with a low 1.5-powered logarithmic overhead. Universality implies that the fat-stack of a given size is nearly the best routing network of that size. The fat-stack is also the minimal universal network in terms of number of links and nodes used. In this paper, we add more analytical proof and report our simulation results. Simulations show that the fat-stack outperforms a mesh-based distributed network of comparable hardware usage. We show how the fat-stack can be an effective benchmark architecture and how to scale the network from a VLSI graph layout to a large-scale distributed topology. Our work helps explain why some deployed networks function in the way they do in terms of routing. It also provides an exemplary network of proven efficiency and scalability for building new distributed systems.
16405002
The fat-stack and universal routing in interconnection networks
This paper shows that a novel network called the fat-stack is universally efficient and is suitable for use as an interconnection network in parallel computers. A requirement for the fat-stack to be universal is that link capacities double up the levels of the network. The fat-stack resembles the fat-tree and the fat-pyramid in hardware structure, but it has unique strengths. It is a construct of an atomic subnetwork unit consisting of one ring and one or more upward links to an upper subnetwork. This simple structure entails easy wirability. The network also uses fewer wires. More importantly, it has the capability to scale up to represent a large-scale distributed network. We developed efficient routing algorithms specific to the fat-stack. Our universality proof shows that a fat-stack variant with increased links and of area @Q(A) can simulate any competing network of area A with O(logA) overhead independently of wire delay. The universality result implies that the augmented fat-stack of a given size is nearly the best routing network of that size. The augmented fat-stack is the minimal universal network for an O(logA) overhead in terms of hardware usage. Actual simulations show that the performance of the augmented fat-stack approaches that of the fat-pyramid and is far higher than that of the fat-tree.
27656613
Multi-level Loop Fusion with Minimal Code Size
17091320
Universal routing in distributed networks
We show that universal routing can be achieved with low overhead in distributed networks. The validity of our results rests on a new network called the fat-stack. We show that from a routing perspective the fat-stack is efficient and is suitable for use as a baseline distributed network We prove that the fat-stack is universal by routing efficiency. A requirement for the fat-stack to be universal is that link capacities double up the levels of the network. We use methods developed in the areas of VLSI and processor interconnect for much of our analysis. Our universality proof shows that a fat-stack of area /spl Theta/(A) can simulate any competing network of area A with O(log/sup 3/2/ A) overhead independently of wire delay. The universality result implies that the fat-stack of a given size is nearly the best routing network of that size. The fat-stack is also the minimal universal network for an O(log/sup 3/2/ A) overhead in terms of number of links.
2853176
Loop Fusion via Retiming for DSP Applications
8321087
Improvements on the WTLS protocol to avoid denial of service attacks
The current WTLS protocol is closely modeled after the well-studied SSL protocol. However, since some differences exist between these two protocols, even if the SSL protocol is secure, the WTLS protocol may not. We propose three kinds of possible Denial of Service (DoS) attacks on the existing WTLS protocol, which can be categorized into two types: memory exhaustion attacks and CPU exhaustion attacks. The first and the second kinds of attacks belong to memory exhaustion attacks, and the third kind of attack is a CPU exhaustion attack. Not only wireless network clients but also Internet clients can launch these three kinds of attacks, which are very simple and effective. Since Internet clients are more powerful in network bandwidth and CPU resources, damages made by these attackers are more serious, which can even make the WTLS server stop providing services for legitimate clients. Client cookies, client puzzles and an application timer is used to improve the current protocol, and our improvements are secure against such attacks.
12064638
SDD: Secure Distributed Diffusion Protocol for Sensor Networks
A sensor network is a collection of tiny sensor nodes, which consists of sensing, data processing and communicating components. Directed Diffusion is an important data-centric routing protocol of sensor networks. In this paper we present the design of a new secure Directed Diffusion protocol (SDD), which provides a secure extension for the Directed Diffusion protocol. We mainly focus on secure routing and give a simple scheme to securely diffuse data. We have not considered with the in-network aggregation as a goal. In order to support the use of SDD for sensor nodes with extremely limited CPU processing capability, we use an efficient one-way chain and do not use asymmetric cryptographic operations in this protocol. Our security analyses show that SDD is robust against any active attackers or compromised nodes in the network.
875545
Multiplex Encryption: A Practical Approach to Encrypting Multi-recipient Emails
Efficiently protecting the privacy of multi-recipient emails is not as trivial as it seems. The approach proposed by S/MIME is to concatenate all ciphertexts. However, it suffers from poor scalability due to its linear computation and communication cost. In this paper, we propose a new practical and secure scheme, called multiplex encryption. By combining the ideas of identity-based mediated RSA and re-encryption mix network, our framework only requires constant computation and communication cost to encrypt a multi-recipient email.
10131512
Identity based proxy-signcryption scheme from pairings
An identity-based cryptosystem is a novel type of public cryptographic scheme in which the public keys of the users are their identities or strings derived from their identities. A signcryption is a primitive that provides private and authenticated delivery of messages between two parties. Proxy signature schemes are variations of ordinary digital signature schemes and have been shown to be useful in many applications. We proposed an identity-based proxy-signcryption scheme from pairings. Also we analyze the proposed scheme from efficiency and security points of view. Heuristic arguments have been given for those security properties. We have shown that the proxy-signcryption scheme is as efficient as ordinary identity-based signcryption schemes under certain circumstances.
1757195
Combining linear discriminant functions with neural networks for supervised learning
A novel supervised learning method is proposed by combining linear discriminant functions with neural networks. The proposed method results in a tree-structured hybrid architecture. Due to constructive learning, the binary tree hierarchical architecture is automatically generated by a controlled growing process for a specific supervised learning task. Unlike the classic decision tree, the linear discriminant functions are merely employed in the intermediate level of the tree for heuristically partitioning a large and complicated task into several smaller and simpler subtasks in the proposed method. These subtasks are dealt with by component neural networks at the leaves of the tree accordingly. For constructive learning, growing and credit-assignment algorithms are developed to serve for the hybrid architecture. The proposed architecture provides an efficient way to apply existing neural networks (e.g. multi-layered perceptron) for solving a large scale problem. We have already applied the proposed method to a universal approximation problem and several benchmark classification problems in order to evaluate its performance. Simulation results have shown that the proposed method yields better results and faster training in comparison with the multilayered perceptron.