arXiv subjects

Emina Soljanin

Publications and source records attributed to Emina Soljanin.

89 records · Page 5Linked to original sources

arXiv2012

Toward Sustainable Networking: Storage Area Networks with Network Coding

This manuscript provides a model to characterize the energy savings of network coded storage (NCS) in storage area networks (SANs). We consider blocking probability of drives as our measure of performance. A mapping technique to analyze SANs as independent M/G/K/K queues is presented, and blocking probabilities for uncoded storage schemes and NCS are derived and compared. We show that coding operates differently than the amalgamation of file chunks and energy savings are shown to scale well with striping number. We illustrate that for enterprise-level SANs energy savings of 20-50% can be realized.

cs.DC↗

arXiv2010

Effects of the Generation Size and Overlap on Throughput and Complexity in Randomized Linear Network Coding

To reduce computational complexity and delay in randomized network coded content distribution, and for some other practical reasons, coding is not performed simultaneously over all content blocks, but over much smaller, possibly overlapping subsets of these blocks, known as generations. A penalty of this strategy is throughput reduction. To analyze the throughput loss, we model coding over generations with random generation scheduling as a coupon collector's brotherhood problem. This model enables us to derive the expected number of coded packets needed for successful decoding of the entire content as well as the probability of decoding failure (the latter only when generations do not overlap) and further, to quantify the tradeoff between computational complexity and throughput. Interestingly, with a moderate increase in the generation size, throughput quickly approaches link capacity. Overlaps between generations can further improve throughput substantially for relatively small generation sizes.

cs.IT↗

arXiv2010

Collecting Coded Coupons over Generations

To reduce computational complexity and delay in randomized network coded content distribution (and for some other practical reasons), coding is not performed simultaneously over all content blocks but over much smaller subsets known as generations. A penalty is throughput reduction. We model coding over generations as the coupon collector's brotherhood problem. This model enables us to theoretically compute the expected number of coded packets needed for successful decoding of the entire content, as well as a bound on the probability of decoding failure, and further, to quantify the tradeoff between computational complexity and throughput. Interestingly, with a moderate increase in the generation size, throughput quickly approaches link capacity. As an additional contribution, we derive new results for the generalized collector's brotherhood problem which can also be used for further study of many other aspects of coding over generations.

cs.IT↗

arXiv2010

Memory Allocation in Distributed Storage Networks

We consider the problem of distributing a file in a network of storage nodes whose storage budget is limited but at least equals to the size file. We first generate $T$ encoded symbols (from the file) which are then distributed among the nodes. We investigate the optimal allocation of $T$ encoded packets to the storage nodes such that the probability of reconstructing the file by using any $r$ out of $n$ nodes is maximized. Since the optimal allocation of encoded packets is difficult to find in general, we find another objective function which well approximates the original problem and yet is easier to optimize. We find the optimal symmetric allocation for all coding redundancy constraints using the equivalent approximate problem. We also investigate the optimal allocation in random graphs. Finally, we provide simulations to verify the theoretical results.

cs.IT↗

arXiv2010

Collecting Coded Coupons over Overlapping Generations

Coding over subsets (known as generations) rather than over all content blocks in P2P distribution networks and other applications is necessary for a number of practical reasons such as computational complexity. A penalty for coding only within generations is an overall throughput reduction. It has been previously shown that allowing contiguous generations to overlap in a head-to-toe manner improves the throughput. We here propose and study a scheme, referred to as the {\it random annex code}, that creates shared packets between any two generations at random rather than only the neighboring ones. By optimizing very few design parameters, we obtain a simple scheme that outperforms both the non-overlapping and the head-to-toe overlapping schemes of comparable computational complexity, both in the expected throughput and in the rate of convergence of the probability of decoding failure to zero. We provide a practical algorithm for accurate analysis of the expected throughput of the random annex code for finite-length information. This algorithm enables us to quantify the throughput vs.computational complexity tradeoff, which is necessary for optimal selection of the scheme parameters.

cs.IT↗

arXiv2010

Rateless Codes for Single-Server Streaming to Diverse Users

We investigate the performance of rateless codes for single-server streaming to diverse users, assuming that diversity in users is present not only because they have different channel conditions, but also because they demand different amounts of information and have different decoding capabilities. The LT encoding scheme is employed. While some users accept output symbols of all degrees and decode using belief propagation, others only collect degree- 1 output symbols and run no decoding algorithm. We propose several performance measures, and optimize the performance of the rateless code used at the server through the design of the code degree distribution. Optimization problems are formulated for the asymptotic regime and solved as linear programming problems. Optimized performance shows great improvement in total bandwidth consumption over using the conventional ideal soliton distribution, or simply sending separately encoded streams to different types of user nodes. Simulation experiments confirm the usability of the optimization results obtained for the asymptotic regime as a guideline for finite-length code design.

cs.IT↗

arXiv2010

Doped Fountain Coding for Minimum Delay Data Collection in Circular Networks

This paper studies decentralized, Fountain and network-coding based strategies for facilitating data collection in circular wireless sensor networks, which rely on the stochastic diversity of data storage. The goal is to allow for a reduced delay collection by a data collector who accesses the network at a random position and random time. Data dissemination is performed by a set of relays which form a circular route to exchange source packets. The storage nodes within the transmission range of the route's relays linearly combine and store overheard relay transmissions using random decentralized strategies. An intelligent data collector first collects a minimum set of coded packets from a subset of storage nodes in its proximity, which might be sufficient for recovering the original packets and, by using a message-passing decoder, attempts recovering all original source packets from this set. Whenever the decoder stalls, the source packet which restarts decoding is polled/doped from its original source node. The random-walk-based analysis of the decoding/doping process furnishes the collection delay analysis with a prediction on the number of required doped packets. The number of doped packets can be surprisingly small when employed with an Ideal Soliton code degree distribution and, hence, the doping strategy may have the least collection delay when the density of source nodes is sufficiently large. Furthermore, we demonstrate that network coding makes dissemination more efficient at the expense of a larger collection delay. Not surprisingly, a circular network allows for a significantly more (analytically and otherwise) tractable strategies relative to a network whose model is a random geometric graph.

cs.IT↗

arXiv2009

Decentralized Coding Algorithms for Distributed Storage in Wireless Sensor Networks

We consider large-scale wireless sensor networks with $n$ nodes, out of which k are in possession, (e.g., have sensed or collected in some other way) k information packets. In the scenarios in which network nodes are vulnerable because of, for example, limited energy or a hostile environment, it is desirable to disseminate the acquired information throughout the network so that each of the n nodes stores one (possibly coded) packet so that the original k source packets can be recovered, locally and in a computationally simple way from any k(1 + ε) nodes for some small ε> 0. We develop decentralized Fountain codes based algorithms to solve this problem. Unlike all previously developed schemes, our algorithms are truly distributed, that is, nodes do not know n, k or connectivity in the network, except in their own neighborhoods, and they do not maintain any routing tables.

cs.IT↗

arXiv2009

Coding Improves the Throughput-Delay Trade-off in Mobile Wireless Networks

We study the throughput-delay performance tradeoff in large-scale wireless ad hoc networks. It has been shown that the per source-destination pair throughput can be improved from Theta(1/sqrt(n log n)) to Theta(1) if nodes are allowed to move and a 2-hop relay scheme is employed. The price paid for such an improvement on throughput is large delay. Indeed, the delay scaling of the 2-hop relay scheme is Theta(n log n) under the random walk mobility model. In this paper, we employ coding techniques to improve the throughput-delay trade-off for mobile wireless networks. For the random walk mobility model, we improve the delay from Theta(n log n) to Theta(n) by employing Reed-Solomon codes. Our approach maintains the diversity gained by mobility while decreasing the delay.

cs.IT↗

arXiv2009

Secure Network Coding for Wiretap Networks of Type II

We consider the problem of securing a multicast network against a wiretapper that can intercept the packets on a limited number of arbitrary network edges of its choice. We assume that the network employs the network coding technique to simultaneously deliver the packets available at the source to all the receivers. We show that this problem can be looked at as a network generalization of the wiretap channel of type II introduced in a seminal paper by Ozarow and Wyner. In particular, we show that the transmitted information can be secured by using the Ozarow-Wyner approach of coset coding at the source on top of the existing network code. This way, we quickly and transparently recover some of the results available in the literature on secure network coding for wiretap networks. Moreover, we derive new bounds on the required alphabet size that are independent of the network size and devise an algorithm for the construction of secure network codes. We also look at the dual problem and analyze the amount of information that can be gained by the wiretapper as a function of the number of wiretapped edges.

cs.IT↗

arXiv2009

Raptor Codes Based Distributed Storage Algorithms for Wireless Sensor Networks

We consider a distributed storage problem in a large-scale wireless sensor network with $n$ nodes among which $k$ acquire (sense) independent data. The goal is to disseminate the acquired information throughout the network so that each of the $n$ sensors stores one possibly coded packet and the original $k$ data packets can be recovered later in a computationally simple way from any $(1+ε)k$ of nodes for some small $ε>0$. We propose two Raptor codes based distributed storage algorithms for solving this problem. In the first algorithm, all the sensors have the knowledge of $n$ and $k$. In the second one, we assume that no sensor has such global information.

cs.IT↗

arXiv2009

Fountain Codes Based Distributed Storage Algorithms for Large-scale Wireless Sensor Networks

We consider large-scale sensor networks with n nodes, out of which k are in possession, (e.g., have sensed or collected in some other way) k information packets. In the scenarios in which network nodes are vulnerable because of, for example, limited energy or a hostile environment, it is desirable to disseminate the acquired information throughout the network so that each of the n nodes stores one (possibly coded) packet and the original k source packets can be recovered later in a computationally simple way from any (1 + ε)k nodes for some small ε> 0. We developed two distributed algorithms for solving this problem based on simple random walks and Fountain codes. Unlike all previously developed schemes, our solution is truly distributed, that is, nodes do not know n, k or connectivity in the network, except in their own neighborhoods, and they do not maintain any routing tables. In the first algorithm, all the sensors have the knowledge of n and k. In the second algorithm, each sensor estimates these parameters through the random walk dissemination. We present analysis of the communication/transmission and encoding/decoding complexity of these two algorithms, and provide extensive simulation results as well

cs.IT↗

arXiv2008

On Wiretap Networks II

We consider the problem of securing a multicast network against a wiretapper that can intercept the packets on a limited number of arbitrary network links of his choice. We assume that the network implements network coding techniques to simultaneously deliver all the packets available at the source to all the destinations. We show how this problem can be looked at as a network generalization of the Ozarow-Wyner Wiretap Channel of type II. In particular, we show that network security can be achieved by using the Ozarow-Wyner approach of coset coding at the source on top of the implemented network code. This way, we quickly and transparently recover some of the results available in the literature on secure network coding for wiretapped networks. We also derive new bounds on the required secure code alphabet size and an algorithm for code construction.

cs.IT↗

arXiv2008

Network Coding Capacity of Random Wireless Networks under a SINR Model

Previous work on network coding capacity for random wired and wireless networks have focused on the case where the capacities of links in the network are independent. In this paper, we consider a more realistic model, where wireless networks are modelled by random geometric graphs with interference and noise. In this model, the capacities of links are not independent. By employing coupling and martingale methods, we show that, under mild conditions, the network coding capacity for random wireless networks still exhibits a concentration behavior around the mean value of the minimum cut.

cs.IT↗

arXiv2007

Network Coding Capacity of Random Wireless Networks under a Signal-to-Interference-and-Noise Model

In this paper, we study network coding capacity for random wireless networks. Previous work on network coding capacity for wired and wireless networks have focused on the case where the capacities of links in the network are independent. In this paper, we consider a more realistic model, where wireless networks are modeled by random geometric graphs with interference and noise. In this model, the capacities of links are not independent. We consider two scenarios, single source multiple destinations and multiple sources multiple destinations. In the first scenario, employing coupling and martingale methods, we show that the network coding capacity for random wireless networks still exhibits a concentration behavior around the mean value of the minimum cut under some mild conditions. Furthermore, we establish upper and lower bounds on the network coding capacity for dependent and independent nodes. In the second one, we also show that the network coding capacity still follows a concentration behavior. Our simulation results confirm our theoretical predictions.

cs.IT↗

arXiv2007

Incremental Redundancy Cooperative Coding for Wireless Networks: Cooperative Diversity, Coding, and Transmission Energy Gain

We study an incremental redundancy (IR) cooperative coding scheme for wireless networks. To exploit the spatial diversity benefit we propose a cluster-based collaborating strategy for a quasi-static Rayleigh fading channel model and based on a network geometric distance profile. Our scheme enhances the network performance by embedding an IR cooperative coding scheme into an existing noncooperative route. More precisely, for each hop, we form a collaborating cluster of M-1 nodes between the (hop) sender and the (hop) destination. The transmitted message is encoded using a mother code and partitioned into M blocks corresponding to the each of M slots. In the first slot, the (hop) sender broadcasts its information by transmitting the first block, and its helpers attempt to relay this message. In the remaining slots, the each of left-over M-1 blocks is sent either through a helper which has successfully decoded the message or directly by the (hop) sender where a dynamic schedule is based on the ACK-based feedback from the cluster. By employing powerful good codes (e.g., turbo codes, LDPC codes, and raptor codes) whose performance is characterized by a threshold behavior, our approach improves the reliability of a multi-hop routing through not only cooperation diversity benefit but also a coding advantage. The study of the diversity and the coding gain of the proposed scheme is based on a new simple threshold bound on the frame-error rate (FER) of maximum likelihood decoding. A average FER upper bound and its asymptotic (in large SNR) version are derived as a function of the average fading channel SNRs and the code threshold.

cs.IT↗

arXiv2001

Compressing Mixed-State Sources by Sending Classical Information

We consider visible compression for discrete memoryless sources of mixed quantum states when only classical information can be sent from Alice to Bob. We assume that Bob knows the source statistics, and that Alice and Bob have identical random number generators. We put in an information theoretic framework some recent results on visible compression for sources of states with commuting density operators, and remove the commutativity requirement. We derive a general achievable compression rate, which is for the noncommutative case still higher than the known lower bound. We also present several related problems of classical information theory, and show how they can be used to answer some questions of the mixed state compression problem.

quant-ph↗