Ion I. Mandoiu

Selecting forwarding neighbors in wireless ad hoc networks

Broadcasting is a fundamental operation which is frequent in wireless ad hoc networks. A simple broadcasting mechanism, known as flooding, is to let every node retransmit the message to all its 1-hop neighbors when receiving the first copy of the message. Despite its simplicity, flooding is very inefficient and can result in high redundancy, contention, and collision. One approach to reducing the redundancy is to let each node forward the message only to a small subset of 1-hop neighbors that cover all of the nodes 2-hop neighbors. In this paper we propose two practical heuristics for selecting the minimum number of forwarding neighbors: an O(nlog n) time algorithm that selects at most 6 times more forwarding neighbors than the optimum, and an O(nlog 2n) time algorithm with an improved approximation ratio of 3, where n is the number of 1- and 2-hop neighbors. The best previously known algorithm, due to Bronnimann and Goodrich [2], guarantees O(1) approximation in O(n3 log n) time.

Symmetric Connectivity with Minimum Power Consumption in Radio Networks

We study the problem of assigning transmission ranges to the nodes of a multi-hop packet radio network (also known as static ad hoc wireless network) so as to minimize the total power consumed under the constraint that enough power is provided to the nodes to ensure that the network is connected. Precisely, we require that the bidirectional links established by the transmission range of every node form a connected graph. We call this problem Min-Power Symmetric Connectivity.

Power efficient range assignment for symmetric connectivity in static ad hoc wireless networks

In this paper we study the problem of assigning transmission ranges to the nodes of a static ad hoc wireless network so as to minimize the total power consumed under the constraint that enough power is provided to the nodes to ensure that the network is connected. We focus on the Min-Power Symmetric Connectivity problem, in which the bidirectional links established by the transmission ranges are required to form a connected graph.Implicit in previous work on transmission range assignment under asymmetric connectivity requirements is the proof that Min-Power Symmetric Connectivity is NP-hard and that the MST algorithm has a performance ratio of 2. In this paper we make the following contributions: (1) we show that the related Min-Power Symmetric Unicast problem can be solved efficiently by a shortest-path computation in an appropriately constructed auxiliary graph; (2) we give an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 35–40 nodes in 1 hour; (3) we establish the similarity between Min-Power Symmetric Connectivity and the classic Steiner Tree problem in graphs, and use this similarity to give a polynomial-time approximation scheme with performance ratio approaching 5/3 as well as a more practical approximation algorithm with approximation factor 11/6; and (4) we give the results of a comprehensive experimental study comparing new and previously proposed heuristics with the above exact and approximation algorithms.

Highly scalable algorithms for rectilinear and octilinear Steiner trees

The rectilinear Steiner minimum tree (RSMT) problem, which asks for a minimum-length interconnection of a given set of terminals in the rectilinear plane, is one of the fundamental problems in electronic design automation. Recently there has been renewed interest in this problem due to the need for highly scalable algorithms able to handle nets with tens of thousands of terminals. In this paper we give a practical O (n log2 n) heuristic for computing near-optimal rectilinear Steiner trees based on a batched version of the greedy triple contraction algorithm of Zelikovsky [21]. Experiments conducted on both random and industry testcases show that our heuristic matches or exceeds the quality of best known RSMT heuristics, e.g., on random instances with more than 100 terminals our heuristic improves over the rectilinear minimum spanning tree by an average of 11%. Moreover, our heuristic has very well scaling runtime, e.g., it can route a 34k-terminals net extracted from a real design in less than 25 seconds compared to over 86 minutes needed by the O(n2) edge-based heuristic of Borah, Owens, and Irwin [3]. Since our heuristic is graph-based, it can be easily modified to handle practical considerations such as routing obstacles, preferred directions, via costs, and octilinear routing - indeed, experimental results show only a small factor increase in runtime when switching from rectilinear to octilinear routing.

The Y-Architecture for On-Chip Interconnect: Analysis and Methodology

The Y-architecture for on-chip interconnect is based on pervasiveuse of 0-, 120-, and 240-degree oriented semi-global and globalwiring. Its use of three uniform directions exploits on-chip routingresources more efficiently than traditional Manhattan wiring architecture.This paper gives in-depth analysis of deployment issues associatedwith the Y-architecture. Our contributions are as follows:(1) We analyze communication capability (throughput of meshes)for different interconnect architectures using a multi-commodityflow approach and a Rentian communication model. Throughput ofthe Y-architecture is largely improved compared to the Manhattanarchitecture, and is close to the throughput of the X-architecture.(2) We propose a symmetrical Y clock tree structure with bettertotal wire length compared to both H and X clock tree structures,and better path length compared to the H tree. (3) We discuss powerdistribution under the Y-architecture, and give analytical and SPICEsimulation results showing that the power network in Y-architecturecan achieve 8.5% less IR drop than an equally-resourced power networkin Manhattan architecture. (4) We propose the use of via tunnelsand banks of via tunnels as a technique for improving routabilityfor Manhattan and Y-architectures.

Identification of mammalian orthologs using local synteny

BackgroundAccurate determination of orthology is central to comparative genomics. For vertebrates in particular, very large gene families, high rates of gene duplication and loss, multiple mechanisms of gene duplication, and high rates of retrotransposition all combine to make inference of orthology between genes difficult. Many methods have been developed to identify orthologous genes, mostly based upon analysis of the inferred protein sequence of the genes. More recently, methods have been proposed that use genomic context in addition to protein sequence to improve orthology assignment in vertebrates. Such methods have been most successfully implemented in fungal genomes and have long been used in prokaryotic genomes, where gene order is far less variable than in vertebrates. However, to our knowledge, no explicit comparison of synteny and sequence based definitions of orthology has been reported in vertebrates, or, more specifically, in mammals.ResultsWe test a simple method for the measurement and utilization of gene order (local synteny) in the identification of mammalian orthologs by investigating the agreement between coding sequence based orthology (Inparanoid) and local synteny based orthology. In the 5 mammalian genomes studied, 93% of the sampled inter-species pairs were found to be concordant between the two orthology methods, illustrating that local synteny is a robust substitute to coding sequence for identifying orthologs. However, 7% of pairs were found to be discordant between local synteny and Inparanoid. These cases of discordance result from evolutionary events including retrotransposition and genome rearrangements.ConclusionsBy analyzing cases of discordance between local synteny and Inparanoid we show that local synteny can distinguish between true orthologs and recent retrogenes, can resolve ambiguous many-to-many orthology relationships into one-to-one ortholog pairs, and might be used to identify cases of non-orthologous gene displacement by retroduplicated paralogs.

Bioinformatics Algorithms: Techniques and Applications

This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, the book covers: general algorithmic techniques, algorithms and tools for genome and sequence analysis, microarray design and analysis, algorithmic issues arising in the analysis of genetic variation across human population, and algorithmic approaches in structural and systems biology.

In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics.

Current methods of structure identification in mass-spectrometry-based nontargeted metabolomics rely on matching experimentally determined features of an unknown compound to those of candidate compounds contained in biochemical databases. A major limitation of this approach is the relatively small number of compounds currently included in these databases. If the correct structure is not present in a database, it cannot be identified, and if it cannot be identified, it cannot be included in a database. Thus, there is an urgent need to augment metabolomics databases with rationally designed biochemical structures using alternative means. Here we present the In Vivo/In Silico Metabolites Database (IIMDB), a database of in silico enzymatically synthesized metabolites, to partially address this problem. The database, which is available at http://metabolomics.pharm.uconn.edu/iimdb/, includes ~23,000 known compounds (mammalian metabolites, drugs, secondary plant metabolites, and glycerophospholipids) collected from existing biochemical databases plus more than 400,000 computationally generated human phase-I and phase-II metabolites of these known compounds. IIMDB features a user-friendly web interface and a programmer-friendly RESTful web service. Ninety-five percent of the computationally generated metabolites in IIMDB were not found in any existing database. However, 21,640 were identical to compounds already listed in PubChem, HMDB, KEGG, or HumanCyc. Furthermore, the vast majority of these in silico metabolites were scored as biological using BioSM, a software program that identifies biochemical structures in chemical structure space. These results suggest that in silico biochemical synthesis represents a viable approach for significantly augmenting biochemical databases for nontargeted metabolomics applications.

Highly scalable algorithms for robust string barcoding

String barcoding is a recently introduced technique for genomic based identification of microorganisms. In this paper, we describe the engineering of highly scalable algorithms for robust string barcoding. Our methods enable distinguisher selection based on whole genomic sequences of hundreds of microorganisms of up to bacterial size, on a well equipped workstation. Experimental results on both randomly generated and NCBI genomic data show that whole-genome based selection results in a number of distinguishers nearly matching the information theoretic lower bounds for the problem.

On the skew-bounded minimum-buffer routing tree problem

Bounding the load capacitance at gate outputs is a standard element in todays electrical correctness methodologies for high-speed digital very large scale integration design. Bounds on load caps improve coupling-noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise (Kahng et al. 1998). For clock and test distribution, an additional design requirement is bounding the buffer skew, i.e., the difference between the maximum and the minimum number of buffers over all of the source-to-sink paths in the routing tree, since buffer skew is one of the main factors affecting delay skew (Tellez and Sarrafzadeh 1997). In this paper, we consider algorithms for buffering a given tree with the minimum number of buffers under given load cap and buffer skew constraints. We show that the greedy algorithm proposed by Tellez and Sarrafzadeh is suboptimal for nonzero buffer-skew bounds and give examples showing that no bottom-up greedy algorithm can achieve optimality. The main contribution of the paper is an optimal dynamic programming algorithm for the problem. Experiments on test cases extracted from recent industrial designs show that the dynamic programming algorithm has practical running time and saves up to 37.5% of the buffers inserted by Tellez and Sarrafzadehs algorithm.