Elastic Entangled Pair and Qubit Resource Management in Quantum Cloud Computing

Quantum cloud computing (QCC) offers a promising approach to efficiently provide quantum computing resources, such as quantum computers, to perform resource-intensive tasks. Like traditional cloud computing platforms, QCC providers can offer both reservation and on-demand plans for quantum resource provisioning to satisfy users' requirements. However, the fluctuations in user demand and quantum circuit requirements are challenging for efficient resource provisioning. Furthermore, in distributed QCC, entanglement routing is a critical component of quantum networks that enables remote entanglement communication between users and QCC providers. Further, maintaining entanglement fidelity in quantum networks is challenging due to the requirement for high-quality entanglement routing, especially when accessing the providers over long distances. To address these challenges, we propose a resource allocation model to provision quantum computing and networking resources. In particular, entangled pairs, entanglement routing, qubit resources, and circuits' waiting time are jointly optimized to achieve minimum total costs. We formulate the proposed model based on the two-stage stochastic programming, which takes into account the uncertainties of fidelity and qubit requirements, and quantum circuits' waiting time. Furthermore, we apply the Benders decomposition algorithm to divide the proposed model into sub-models to be solved simultaneously. Experimental results demonstrate that our model can achieve the optimal total costs and reduce total costs at most 49.43\% in comparison to the baseline model.Comment: 30 pages and 20 figure

Topological Characterization of Hamming and Dragonfly Networks and its Implications on Routing

Current HPC and datacenter networks rely on large-radix routers. Hamming graphs (Cartesian products of complete graphs) and dragonflies (two-level direct networks with nodes organized in groups) are some direct topologies proposed for such networks. The original definition of the dragonfly topology is very loose, with several degrees of freedom such as the inter- and intra-group topology, the specific global connectivity and the number of parallel links between groups (or trunking level). This work provides a comprehensive analysis of the topological properties of the dragonfly network, providing balancing conditions for network dimensioning, as well as introducing and classifying several alternatives for the global connectivity and trunking level. From a topological study of the network, it is noted that a Hamming graph can be seen as a canonical dragonfly topology with a large level of trunking. Based on this observation and by carefully selecting the global connectivity, the Dimension Order Routing (DOR) mechanism safely used in Hamming graphs is adapted to dragonfly networks with trunking. The resulting routing algorithms approximate the performance of minimal, non-minimal and adaptive routings typically used in dragonflies, but without requiring virtual channels to avoid packet deadlock, thus allowing for lower-cost router implementations. This is obtained by selecting properly the link to route between groups, based on a graph coloring of the network routers. Evaluations show that the proposed mechanisms are competitive to traditional solutions when using the same number of virtual channels, and enable for simpler implementations with lower cost. Finally, multilevel dragonflies are discussed, considering how the proposed mechanisms could be adapted to them

Optimization of communication intensive applications on HPC networks

Communication is a necessary but overhead inducing component of parallel programming. Its impact on application design and performance is due to several related aspects of a parallel job execution: network topology, routing protocol, suitability of algorithm being used to the network, job placement, etc. This thesis is aimed at developing an understanding of how communication plays out on networks of high performance computing systems and exploring methods that can be used to improve communication performance of large scale applications. Broadly speaking, three topics have been studied in detail in this thesis. The first of these topics is task mapping and job placement on practical installations of torus and dragonfly networks. Next, use of supervised learning algorithms for conducting diagnostic studies of how communication evolves on networks is explored. Finally, efficacy of packet-level simulations for prediction-based studies of communication performance on different networks using different network parameters is analyzed. The primary contribution of this thesis is development of scalable diagnostic and prediction methods that can assist in the process of network designing, adapting applications to future systems, and optimizing execution of applications on existing systems. These meth- ods include a supervised learning approach, a functional modeling tool (called Damselfly), and a PDES-based packet level simulator (called TraceR), all of which are described in this thesis

Routing and privacy protection in human associated delay tolerant networks

This thesis proposes Human Associated Delay Tolerant Networks, where data communications among mobile nodes are determined by human social behaviours. Three models are proposed to handle the social attributes effect on data forwarding, the time impact on nodes’ movement and the privacy protection issue when social attributes are introduced

Towards Trustworthy, Efficient and Scalable Distributed Wireless Systems

Advances in wireless technologies have enabled distributed mobile devices to connect with each other to form distributed wireless systems. Due to the absence of infrastructure, distributed wireless systems require node cooperation in multi-hop routing. However, the openness and decentralized nature of distributed wireless systems where each node labors under a resource constraint introduces three challenges: (1) cooperation incentives that effectively encourage nodes to offer services and thwart the intentions of selfish and malicious nodes, (2) cooperation incentives that are efficient to deploy, use and maintain, and (3) routing to efficiently deliver messages with less overhead and lower delay. While most previous cooperation incentive mechanisms rely on either a reputation system or a price system, neither provides sufficiently effective cooperation incentives nor efficient resource consumption. Also, previous routing algorithms are not sufficiently efficient in terms of routing overhead or delay. In this research, we propose mechanisms to improve the trustworthiness, scalability, and efficiency of the distributed wireless systems. Regarding trustworthiness, we study previous cooperation incentives based on game theory models. We then propose an integrated system that combines a reputation system and a price system to leverage the advantages of both methods to provide trustworthy services. Analytical and simulation results show higher performance for the integrated system compared to the other two systems in terms of the effectiveness of the cooperation incentives and detection of selfish nodes. Regarding scalability in a large-scale system, we propose a hierarchical Account-aided Reputation Management system (ARM) to efficiently and effectively provide cooperation incentives with small overhead. To globally collect all node reputation information to accurately calculate node reputation information and detect abnormal reputation information with low overhead, ARM builds a hierarchical locality-aware Distributed Hash Table (DHT) infrastructure for the efficient and integrated operation of both reputation systems and price systems. Based on the DHT infrastructure, ARM can reduce the reputation management overhead in reputation and price systems. We also design a distributed reputation manager auditing protocol to detect a malicious reputation manager. The experimental results show that ARM can detect the uncooperative nodes that gain fraudulent benefits while still being considered as trustworthy in previous reputation and price systems. Also, it can effectively identify misreported, falsified, and conspiratorial information, providing accurate node reputations that truly reflect node behaviors. Regarding an efficient distributed system, we propose a social network and duration utility-based distributed multi-copy routing protocol for delay tolerant networks based on the ARM system. The routing protocol fully exploits node movement patterns in the social network to increase delivery throughput and decrease delivery delay while generating low overhead. The simulation results show that the proposed routing protocol outperforms the epidemic routing and spray and wait routing in terms of higher message delivery throughput, lower message delivery delay, lower message delivery overhead, and higher packet delivery success rate. The three components proposed in this dissertation research improve the trustworthiness, scalability, and efficiency of distributed wireless systems to meet the requirements of diversified distributed wireless applications

Scheduling algorithms for throughput maximization in data networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 215-226).This thesis considers the performance implications of throughput optimal scheduling in physically and computationally constrained data networks. We study optical networks, packet switches, and wireless networks, each of which has an assortment of features and constraints that challenge the design decisions of network architects. In this work, each of these network settings are subsumed under a canonical model and scheduling framework. Tools of queueing analysis are used to evaluate network throughput properties, and demonstrate throughput optimality of scheduling and routing algorithms under stochastic traffic. Techniques of graph theory are used to study network topologies having desirable throughput properties. Combinatorial algorithms are proposed for efficient resource allocation. In the optical network setting, the key enabling technology is wavelength division multiplexing (WDM), which allows each optical fiber link to simultaneously carry a large number of independent data streams at high rate. To take advantage of this high data processing potential, engineers and physicists have developed numerous technologies, including wavelength converters, optical switches, and tunable transceivers.(cont.) While the functionality provided by these devices is of great importance in capitalizing upon the WDM resources, a major challenge exists in determining how to configure these devices to operate efficiently under time-varying data traffic. In the WDM setting, we make two main contributions. First, we develop throughput optimal joint WDM reconfiguration and electronic-layer routing algorithms, based on maxweight scheduling. To mitigate the service disruption associated with WDM reconfiguration, our algorithms make decisions at frame intervals. Second, we develop analytic tools to quantify the maximum throughput achievable in general network settings. Our approach is to characterize several geometric features of the maximum region of arrival rates that can be supported in the network. In the packet switch setting, we observe through numerical simulation the attractive throughput properties of a simple maximal weight scheduler. Subsequently, we consider small switches, and analytically demonstrate the attractive throughput properties achievable using maximal weight scheduling. We demonstrate that such throughput properties may not be sustained in larger switches.(cont.) In the wireless network setting, mesh networking is a promising technology for achieving connectivity in local and metropolitan area networks. Wireless access points and base stations adhering to the IEEE 802.11 wireless networking standard can be bought off the shelf at little cost, and can be configured to access the Internet in minutes. With ubiquitous low-cost Internet access perceived to be of tremendous societal value, such technology is naturally garnering strong interest. Enabling such wireless technology is thus of great importance. An important challenge in enabling mesh networks, and many other wireless network applications, results from the fact that wireless transmission is achieved by broadcasting signals through the air, which has the potential for interfering with other parts of the network. Furthermore, the scarcity of wireless transmission resources implies that link activation and packet routing should be effected using simple distributed algorithms. We make three main contributions in the wireless setting. First, we determine graph classes under which simple, distributed, maximal weight schedulers achieve throughput optimality.(cont.) Second, we use this acquired knowledge of graph classes to develop combinatorial algorithms, based on matroids, for allocating channels to wireless links, such that each channel can achieve maximum throughput using simple distributed schedulers. Third, we determine new conditions under which distributed algorithms for joint link activation and routing achieve throughput optimality.by Andrew Brzezinski.Ph.D

Journal of Telecommunications and Information Technology

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Multi-hop all-to-all optical routings in Cartesian product networks

This paper considers the wavelength assignment problem for Cartesian product networks with multi-hops. An upper bound of the (uniform) wavelength index for Cartesian product networks with single-hop is established. This result leads to a consequence for the nth power of an arbitrary network with k-hops. In particular. if k = 1, this bound partially generalizes the results of Pankaj [R.K. Pankaj, Architectures for linear lightwave networks, PhD thesis, Dept. of Electrical Engineering and Computer Science, MIT, Cambridge, MA, 1992], Bermond et al. [J.-C. Bermond, L. Gargano, S. Perennes, A.A. Rescigno, U. Vaccaro, Efficient collective communication in optical networks, Theoret. Comput. Sci. 233 (2000) 165-189] and Beauquier [B. Beauquier, All-to-all communication for some wavelength-routed all-optical networks, Networks 33 (1999) 179-187] for hypercubes and Hamming graphs. As an application, a tight upper bound for Hamming graph with k hops is established and a corresponding open problem is also proposed. (C) 2008 Elsevier B.V. All rights reserved

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

On strong fault tolerance (or strong Menger-connectivity) of multicomputer networks

As the size of networks increases continuously, dealing with networks with faulty nodes becomes unavoidable. In this dissertation, we introduce a new measure for network fault tolerance, the strong fault tolerance (or strong Menger-connectivity)in multicomputer networks, and study the strong fault tolerance for popular multicomputer network structures. Let G be a network in which all nodes have degree d. We say that G is strongly fault tolerant if it has the following property: Let Gf be a copy of G with at most d - 2 faulty nodes. Then for any pair of non-faulty nodes u and v in Gf , there are min{degf (u), degf (v)} node-disjoint paths in Gf from u to v, where degf (u) and degf (v) are the degrees of the nodes u and v in Gf, respectively. First we study the strong fault tolerance for the popular network structures such as star networks and hypercube networks. We show that the star networks and the hypercube networks are strongly fault tolerant and develop efficient algorithms that construct the maximum number of node-disjoint paths of nearly optimal or optimal length in these networks when they contain faulty nodes. Our algorithms are optimal in terms of their time complexity. In addition to studying the strong fault tolerance, we also investigate a more realistic concept to describe the ability of networks for tolerating faults. The traditional definition of fault tolerance, sustaining at most d - 1faulty nodes for a regular graph G of degree d, reflects a very rare situation. In many cases, there is a chance that a routing path between two given nodes can be constructed though the network may have more faulty nodes than its degree. In this dissertation, we study the fault tolerance of hypercube networks under a probability model. When each node of the n-dimensional hypercube network has an independent failure probability p, we develop algorithms that, with very high probability, can construct a fault-free path when the hypercube network can sustain up to 2np faulty nodes