Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601049
F. Soldo, Karim El Defrawy, A. Markopoulou, B. Krishnamurthy, Jacobus van der Merwe
There is a large and increasing amount of unwanted traffic on the Internet today, including phishing, spam, and distributed denial-of-service attacks. One way to deal with this problem is to filter unwanted traffic at the routers based on source IP addresses. Because of the limited number of available filters in the routers today, aggregation is used in practice: a single filter describes and blocks an entire range of IP addresses. This results in blocking of all (unwanted and wanted) traffic generated from hosts with IP addresses in that range. In this paper, we develop a family of algorithms that, given a blacklist containing the source IP addresses of unwanted traffic and a constraint on the number of filters, construct a set of filtering rules that optimize the tradeoff between the unwanted and legitimate traffic that is blocked. We show that our algorithms are optimal and also computationally efficient. Furthermore, we demonstrate that they are particularly beneficial when applied to realistic distributions of sources of unwanted traffic, which are known to exhibit spatial and temporal clustering.
{"title":"Filtering sources of unwanted traffic","authors":"F. Soldo, Karim El Defrawy, A. Markopoulou, B. Krishnamurthy, Jacobus van der Merwe","doi":"10.1109/ITA.2008.4601049","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601049","url":null,"abstract":"There is a large and increasing amount of unwanted traffic on the Internet today, including phishing, spam, and distributed denial-of-service attacks. One way to deal with this problem is to filter unwanted traffic at the routers based on source IP addresses. Because of the limited number of available filters in the routers today, aggregation is used in practice: a single filter describes and blocks an entire range of IP addresses. This results in blocking of all (unwanted and wanted) traffic generated from hosts with IP addresses in that range. In this paper, we develop a family of algorithms that, given a blacklist containing the source IP addresses of unwanted traffic and a constraint on the number of filters, construct a set of filtering rules that optimize the tradeoff between the unwanted and legitimate traffic that is blocked. We show that our algorithms are optimal and also computationally efficient. Furthermore, we demonstrate that they are particularly beneficial when applied to realistic distributions of sources of unwanted traffic, which are known to exhibit spatial and temporal clustering.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117134456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601055
Fan Zhang, H. Pfister
Compressed sensing (CS) is a relatively new area of signal processing and statistics that focuses on signal reconstruction from a small number of linear (e.g., dot product) measurements. In this paper, we analyze CS using tools from coding theory because CS can also be viewed as syndrome-based source coding of sparse vectors using linear codes over real numbers. While coding theory does not typically deal with codes over real numbers, there is actually a very close relationship between CS and error-correcting codes over large discrete alphabets. This connection leads naturally to new reconstruction methods and analysis. In some cases, the resulting methods provably require many fewer measurements than previous approaches.
{"title":"Compressed sensing and linear codes over real numbers","authors":"Fan Zhang, H. Pfister","doi":"10.1109/ITA.2008.4601055","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601055","url":null,"abstract":"Compressed sensing (CS) is a relatively new area of signal processing and statistics that focuses on signal reconstruction from a small number of linear (e.g., dot product) measurements. In this paper, we analyze CS using tools from coding theory because CS can also be viewed as syndrome-based source coding of sparse vectors using linear codes over real numbers. While coding theory does not typically deal with codes over real numbers, there is actually a very close relationship between CS and error-correcting codes over large discrete alphabets. This connection leads naturally to new reconstruction methods and analysis. In some cases, the resulting methods provably require many fewer measurements than previous approaches.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120950355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601088
Yang Yang, Zixiang Xiong
Wagner et al. recently characterized the rate region for the quadratic Gaussian two-terminal source coding problem. They also show that the Berger-Tung sum-rate bound is tight in the symmetric case, where all sources are positively symmetric and all target distortions are equal. This work studies the sum-rate loss of quadratic Gaussian direct multiterminal source coding. We first give the minimum sum-rate for joint encoding of Gaussian sources in the symmetric case, we than show that the supremum of the sum-rate loss due to distributed encoding in this case is 1/2 log2 5/4 = 0.161 b/s when L = 2 and increases in the order of radic(L)/2 log2 e b/s as the number of terminals L goes to infinity. The supremum sum-rate loss of 0.161 b/s in the symmetric case equals to that in general quadratic Gaussian two-terminal source coding without the symmetric assumption. It is conjectured that this equality holds for any number of terminals.
Wagner等人最近对二次高斯双端源编码问题的速率区域进行了表征。他们还表明，在对称情况下，所有源都是正对称的，所有目标畸变都是相等的，Berger-Tung和速率界是紧的。本文研究了二次高斯直接多端信源编码的和率损耗。我们首先给出了对称情况下高斯源联合编码的最小和速率，然后证明了在这种情况下，分布式编码导致的和速率损失的最大值是1/2 log2 5/4 = 0.161 b/s，并且随着终端数L趋于无穷，以根号(L)/2 log2 e /s的顺序增加。对称情况下的最大和速率损耗为0.161 b/s，与一般二次高斯双端码源编码不对称情况下的最大和速率损耗相等。据推测，这个等式对任意数量的终端都成立。
{"title":"The supremum sum-rate loss of quadratic Gaussian direct multiterminal source coding","authors":"Yang Yang, Zixiang Xiong","doi":"10.1109/ITA.2008.4601088","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601088","url":null,"abstract":"Wagner et al. recently characterized the rate region for the quadratic Gaussian two-terminal source coding problem. They also show that the Berger-Tung sum-rate bound is tight in the symmetric case, where all sources are positively symmetric and all target distortions are equal. This work studies the sum-rate loss of quadratic Gaussian direct multiterminal source coding. We first give the minimum sum-rate for joint encoding of Gaussian sources in the symmetric case, we than show that the supremum of the sum-rate loss due to distributed encoding in this case is 1/2 log2 5/4 = 0.161 b/s when L = 2 and increases in the order of radic(L)/2 log2 e b/s as the number of terminals L goes to infinity. The supremum sum-rate loss of 0.161 b/s in the symmetric case equals to that in general quadratic Gaussian two-terminal source coding without the symmetric assumption. It is conjectured that this equality holds for any number of terminals.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121332222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601062
Yang Han, W. Ryan
One of the most significant impediments to the use of LDPC codes in many communication and storage systems is the error-rate floor phenomenon associated with their iterative decoders. The error floor has been attributed to certain subgraphs of an LDPC codepsilas Tanner graph induced by so-called trapping sets. We show in this paper that once we identify the trapping sets of an LDPC code of interest, a sum-product algorithm (SPA) decoder can be custom-designed to yield floors that are orders of magnitude lower than the conventional SPA decoder. We present three classes of such decoders: (1) a bi-mode decoder, (2) a bit-pinning decoder which utilizes one or more outer algebraic codes, and (3) three generalized-LDPC decoders. We demonstrate the effectiveness of these decoders for two codes, the rate-1/2 (2640,1320) Margulis code which is notorious for its floors and a rate-0.3 (640,192) quasi-cyclic code which has been devised for this study. Although the paper focuses on these two codes, the decoder design techniques presented are fully generalizable to any LDPC code.
{"title":"LDPC decoder strategies for achieving low error floors","authors":"Yang Han, W. Ryan","doi":"10.1109/ITA.2008.4601062","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601062","url":null,"abstract":"One of the most significant impediments to the use of LDPC codes in many communication and storage systems is the error-rate floor phenomenon associated with their iterative decoders. The error floor has been attributed to certain subgraphs of an LDPC codepsilas Tanner graph induced by so-called trapping sets. We show in this paper that once we identify the trapping sets of an LDPC code of interest, a sum-product algorithm (SPA) decoder can be custom-designed to yield floors that are orders of magnitude lower than the conventional SPA decoder. We present three classes of such decoders: (1) a bi-mode decoder, (2) a bit-pinning decoder which utilizes one or more outer algebraic codes, and (3) three generalized-LDPC decoders. We demonstrate the effectiveness of these decoders for two codes, the rate-1/2 (2640,1320) Margulis code which is notorious for its floors and a rate-0.3 (640,192) quasi-cyclic code which has been devised for this study. Although the paper focuses on these two codes, the decoder design techniques presented are fully generalizable to any LDPC code.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129147113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601087
B. Xie, R. Wesel
There are numerous notions of symmetry for discrete memoryless channels. A common goal of these various definitions is that the capacity may be easily computed once the channel is declared to be symmetric. In this paper we focus on a class of definitions of symmetry characterized by the invariance of the channel mutual information over a group of permutations of the input distribution. For definitions of symmetry within this class, we give a simple proof of the optimality of the uniform distribution. The fundamental channels are all symmetric with a general enough definition of symmetry. This paper provides a definition of symmetry that covers these fundamental channels along with a proof that is simple enough to find itself on the chalkboard of even the most introductory class in information theory.
{"title":"A mutual information invariance approach to symmetry in discrete memoryless channels","authors":"B. Xie, R. Wesel","doi":"10.1109/ITA.2008.4601087","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601087","url":null,"abstract":"There are numerous notions of symmetry for discrete memoryless channels. A common goal of these various definitions is that the capacity may be easily computed once the channel is declared to be symmetric. In this paper we focus on a class of definitions of symmetry characterized by the invariance of the channel mutual information over a group of permutations of the input distribution. For definitions of symmetry within this class, we give a simple proof of the optimality of the uniform distribution. The fundamental channels are all symmetric with a general enough definition of symmetry. This paper provides a definition of symmetry that covers these fundamental channels along with a proof that is simple enough to find itself on the chalkboard of even the most introductory class in information theory.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130613276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601098
M. Levorato, S. Tomasin, M. Zorzi
In this paper we present a recursive algorithm to compute some important performance metrics for wireless networks, such as throughput, channel occupancy, average number of packets in the queue and service time. Our model comprises packet queuing, channel access contention, backoff and hybrid automatic retransmission request (HARQ) error control. The analysis is carried out recursively to reduce the computational complexity and makes use of semi-Markov processes and renewal theory. We present results showing that the proposed model is able to accurately predict the aforementioned metrics even for networks with many nodes, where traditional analysis requires infeasible complexity to account for the overall network status.
{"title":"Recursive analysis of ad hoc networks with packet queueing, channel contention and hybrid ARQ","authors":"M. Levorato, S. Tomasin, M. Zorzi","doi":"10.1109/ITA.2008.4601098","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601098","url":null,"abstract":"In this paper we present a recursive algorithm to compute some important performance metrics for wireless networks, such as throughput, channel occupancy, average number of packets in the queue and service time. Our model comprises packet queuing, channel access contention, backoff and hybrid automatic retransmission request (HARQ) error control. The analysis is carried out recursively to reduce the computational complexity and makes use of semi-Markov processes and renewal theory. We present results showing that the proposed model is able to accurately predict the aforementioned metrics even for networks with many nodes, where traditional analysis requires infeasible complexity to account for the overall network status.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121333936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601082
T. Tjalkens
The author consider a binary classification problem with a feature vector of high dimensionality. Spam mail filters are a popular example hereof. A Bayesian approach requires us to estimate the probability of a feature vector given the class of the object. Due to the size of the feature vector this is an unfeasible task. A useful approach is to split the feature space into several (conditionally) independent subspaces. This results in a new problem, namely how to find the ldquobestrdquo subdivision. In this paper the author consider a weighing approach that will perform (asymptotically) as good as the best subdivision and still has a manageable complexity.
{"title":"Prediction and modeling with partial dependencies","authors":"T. Tjalkens","doi":"10.1109/ITA.2008.4601082","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601082","url":null,"abstract":"The author consider a binary classification problem with a feature vector of high dimensionality. Spam mail filters are a popular example hereof. A Bayesian approach requires us to estimate the probability of a feature vector given the class of the object. Due to the size of the feature vector this is an unfeasible task. A useful approach is to split the feature space into several (conditionally) independent subspaces. This results in a new problem, namely how to find the ldquobestrdquo subdivision. In this paper the author consider a weighing approach that will perform (asymptotically) as good as the best subdivision and still has a manageable complexity.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131384211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601086
N. Prasad, Xiaodong Wang
We consider the problem of rate allocation in classical as well as generalized multiuser cognitive radio systems. Each user intends to communicate with its designated receiver and all receivers employ successive group decoders with specified complexity constraints. Rate allocations in the classical case are obtained by using algorithms designed for a fi user Gaussian Interference Channel (GIC). In the generalized cognitive radio system the transmission rates of the primary users are assumed to be pre-determined such that each primary user is decodable at its (primary) receiver in the GIC consisting only of the primary transmitter-receiver pairs. We investigate the problem of selecting an active set of secondary users that are allowed to co-exist with the primary users and allocating rates to them under the constraints that each primary user achieves its pre-determined rate and no primary receiver decodes any secondary user. Each secondary receiver however is free to decode any other user whose codebook it is aware of. The key feature of the rate allocation algorithms we design is that inspite of using distributed and low-complexity ldquogreedyrdquo sub-routines, they can achieve globally optimal solutions.
{"title":"Rate allocation in multiuser cognitive radio systems with successive group decoding","authors":"N. Prasad, Xiaodong Wang","doi":"10.1109/ITA.2008.4601086","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601086","url":null,"abstract":"We consider the problem of rate allocation in classical as well as generalized multiuser cognitive radio systems. Each user intends to communicate with its designated receiver and all receivers employ successive group decoders with specified complexity constraints. Rate allocations in the classical case are obtained by using algorithms designed for a fi user Gaussian Interference Channel (GIC). In the generalized cognitive radio system the transmission rates of the primary users are assumed to be pre-determined such that each primary user is decodable at its (primary) receiver in the GIC consisting only of the primary transmitter-receiver pairs. We investigate the problem of selecting an active set of secondary users that are allowed to co-exist with the primary users and allocating rates to them under the constraints that each primary user achieves its pre-determined rate and no primary receiver decodes any secondary user. Each secondary receiver however is free to decode any other user whose codebook it is aware of. The key feature of the rate allocation algorithms we design is that inspite of using distributed and low-complexity ldquogreedyrdquo sub-routines, they can achieve globally optimal solutions.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127803344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601027
M. Effros
The author presents new algorithms for fixed-rate multiple description and multiresolution scalar quantizer design. The algorithms both run in time polynomial in the size of the source alphabet and guarantee globally optimal solutions. To the authorpsilas knowledge, these are the first globally optimal design algorithms for multiple description and multiresolution quantizers.
{"title":"Optimal multiple description and multiresolution scalar quantizer design","authors":"M. Effros","doi":"10.1109/ITA.2008.4601027","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601027","url":null,"abstract":"The author presents new algorithms for fixed-rate multiple description and multiresolution scalar quantizer design. The algorithms both run in time polynomial in the size of the source alphabet and guarantee globally optimal solutions. To the authorpsilas knowledge, these are the first globally optimal design algorithms for multiple description and multiresolution quantizers.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115926131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-08-15DOI: 10.1109/ITA.2008.4601073
O. Shental, Danny Bickson, Paul H. Siegel, Jack K. Wolf, D. Dolev
We develop an efficient distributed message-passing solution for systems of linear equations based upon Gaussian belief propagation that does not involve direct matrix inversion.
我们开发了一种基于高斯信念传播的线性方程组的高效分布式消息传递解，该解不涉及直接矩阵反演。
{"title":"A message-passing solver for linear systems","authors":"O. Shental, Danny Bickson, Paul H. Siegel, Jack K. Wolf, D. Dolev","doi":"10.1109/ITA.2008.4601073","DOIUrl":"https://doi.org/10.1109/ITA.2008.4601073","url":null,"abstract":"We develop an efficient distributed message-passing solution for systems of linear equations based upon Gaussian belief propagation that does not involve direct matrix inversion.","PeriodicalId":345196,"journal":{"name":"2008 Information Theory and Applications Workshop","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124382475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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