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Vijay P. Kumar - One of the best experts on this subject based on the ideXlab platform.
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Explicit MSR Codes with Optimal Access, Optimal Sub-Packetization and Small Field Size for $d=k+1, k+2, k+3$
2018 IEEE International Symposium on Information Theory (ISIT), 2018Co-Authors: Myna Vajha, Balaji Srinivasan Babu, Vijay P. KumarAbstract:This paper presents the construction of an explicit, optimal-access, high-rate MSR code for any (n, k, d=k+ 1, k+2, k+3) parameters over the finite field \mathbbFQ having sub-Packetization α = q[n/(q)], where q=d-k+1 and Q=O(n). The sub-Packetization of the current construction meets the lower bound proven in a recent work by Balaji et al. in [1]. To our understanding the codes presented in this paper are the first explicit constructions of MSR codes with having optimal sub-Packetization, optimal access and small field size.
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A Tight Lower Bound on the Sub- Packetization Level of Optimal-Access MSR and MDS Codes
2018 IEEE International Symposium on Information Theory (ISIT), 2018Co-Authors: S. B. Balaji, Vijay P. KumarAbstract:The first focus of the present paper, is on lower bounds on the sub-Packetization level α of an MSR code that is capable of carrying out repair in help-by-transfer fashion (also called optimal-access property). We prove here a lower bound on α which is shown to be tight for the case d=(n-1) by comparing with recent code constructions in the literature. We also extend our results to an [n, k] MDS code over the vector alphabet. Our objective even here, is on lower bounds on the sub-Packetization level α of an MDS code that can carry out repair of any node in a subset of w nodes, 1 ≤ w ≤ (n-1) where each node is repaired (linear repair) by help-by-transfer with minimum repair bandwidth. We prove a lower bound on α for the case of d=(n-1). This bound holds for any w( ≤ n-1) and is shown to be tight, again by comparing with recent code constructions in the literature. Also provided, are bounds for the case . We study the form of a vector MDS code having the property that we can repair failed nodes belonging to a fixed set of Q nodes with minimum repair bandwidth and in optimal-access fashion, and which achieve our lower bound on sub-Packetization level α. It turns out interestingly, that such a code must necessarily have a coupled-layer structure, similar to that of the Ye-Barg code.
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explicit msr codes with optimal access optimal sub Packetization and small field size for d k 1 k 2 k 3
International Symposium on Information Theory, 2018Co-Authors: Myna Vajha, Balaji Srinivasan Babu, Vijay P. KumarAbstract:This paper presents the construction of an explicit, optimal-access, high-rate MSR code for any $(n, k, d=k+ 1, k+2, k+3)$ parameters over the finite field $\mathbb{F}_{Q}$ having sub-Packetization $\alpha=q^{\lceil\frac{n}{\mathrm{q}}\rceil}$ , where $q=d-k+1$ and $Q=O(n)$ . The sub-Packetization of the current construction meets the lower bound proven in a recent work by Balaji et al. in [1]. To our understanding the codes presented in this paper are the first explicit constructions of MSR codes with $d having optimal sub-Packetization, optimal access and small field size.
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a tight lower bound on the sub Packetization level of optimal access msr and mds codes
International Symposium on Information Theory, 2018Co-Authors: S. B. Balaji, Vijay P. KumarAbstract:The first focus of the present paper, is on lower bounds on the sub-Packetization level $\alpha$ of an MSR code that is capable of carrying out repair in help-by-transfer fashion (also called optimal-access property). We prove here a lower bound on $\alpha$ which is shown to be tight for the case $d=(n-1)$ by comparing with recent code constructions in the literature. We also extend our results to an $[n, k]$ MDS code over the vector alphabet. Our objective even here, is on lower bounds on the sub-Packetization level $\alpha$ of an MDS code that can carry out repair of any node in a subset of $w$ nodes, $1\leq w\leq(n-1)$ where each node is repaired (linear repair) by help-by-transfer with minimum repair bandwidth. We prove a lower bound on $\alpha$ for the case of $d=(n-1)$ . This bound holds for any $w(\leq n-1)$ and is shown to be tight, again by comparing with recent code constructions in the literature. Also provided, are bounds for the case $d . We study the form of a vector MDS code having the property that we can repair failed nodes belonging to a fixed set of $Q$ nodes with minimum repair bandwidth and in optimal-access fashion, and which achieve our lower bound on sub-Packetization level $\alpha$ . It turns out interestingly, that such a code must necessarily have a coupled-layer structure, similar to that of the Ye-Barg code.
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explicit msr codes with optimal access optimal sub Packetization and small field size for d k 1 k 2 k 3
arXiv: Information Theory, 2018Co-Authors: Myna Vajha, Balaji Srinivasan Babu, Vijay P. KumarAbstract:This paper presents the construction of an explicit, optimal-access, high-rate MSR code for any $(n,k,d=k+1,k+2,k+3)$ parameters over the finite field $\fQ$ having sub-Packetization $\alpha = q^{\lceil\frac{n}{q}\rceil}$, where $q=d-k+1$ and $Q = O(n)$. The sub-Packetization of the current construction meets the lower bound proven in a recent work by Balaji et al. in \cite{BalKum}. To our understanding the codes presented in this paper are the first explicit constructions of MSR codes with $d<(n-1)$ having optimal sub-Packetization, optimal access and small field size.
Jingke Xu - One of the best experts on this subject based on the ideXlab platform.
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the optimal sub Packetization of linear capacity achieving pir schemes with colluding servers
IEEE Transactions on Information Theory, 2019Co-Authors: Zhifang Zhang, Jingke XuAbstract:Suppose $M$ records are replicated in $N$ servers (each storing all $M$ records), a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a $T$ -private information retrieval (PIR) scheme. In practice, capacity-achieving and small sub-Packetization are both desired for PIR schemes, because the former implies the highest download rate and the latter means simple realization. Meanwhile, sub-Packetization is the key technique for achieving capacity. In this paper, we characterize the optimal sub-Packetization for linear capacity-achieving $T$ -PIR schemes. First, a lower bound on the sub-Packetization $L$ for linear capacity-achieving $T$ -PIR schemes is proved, i.e., $L\geq dn^{M-1}$ , where $d={\mathrm{ gcd}}(N,T)$ and $n=N/d$ . Then, for general values of $M$ and $N>T\geq 1$ , a linear capacity-achieving $T$ -PIR scheme with sub-Packetization $dn^{M-1}$ is designed. Comparing with the first capacity-achieving $T$ -PIR scheme given by Sun and Jafar in 2016, our scheme reduces the sub-Packetization from $N^{M}$ to the optimal and further reduces the field size by a factor of $Nd^{M-2}$ .
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The Optimal Sub-Packetization of Linear Capacity-Achieving PIR Schemes With Colluding Servers
IEEE Transactions on Information Theory, 2019Co-Authors: Zhifang Zhang, Jingke XuAbstract:Suppose M records are replicated in N servers (each storing all M records), a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to T servers. A scheme designed for this purpose is called a T-private information retrieval (PIR) scheme. In practice, capacity-achieving and small sub-Packetization are both desired for PIR schemes, because the former implies the highest download rate and the latter means simple realization. Meanwhile, sub-Packetization is the key technique for achieving capacity. In this paper, we characterize the optimal sub-Packetization for linear capacity-achieving T-PIR schemes. First, a lower bound on the sub-Packetization L for linear capacity-achieving T-PIR schemes is proved, i.e., L ≥ dnM-1, where d = gcd(N, T) and n = N/d. Then, for general values of M and N > T ≥ 1, a linear capacity-achieving T-PIR scheme with sub-Packetization dnM-1 is designed. Comparing with the first capacity-achieving T-PIR scheme given by Sun and Jafar in 2016, our scheme reduces the sub-Packetization from NM to the optimal and further reduces the field size by a factor of NdM-2.
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on sub Packetization and access number of capacity achieving pir schemes for mds coded non colluding servers
Science in China Series F: Information Sciences, 2018Co-Authors: Jingke Xu, Zhifang ZhangAbstract:Consider the problem of private information retrieval (PIR) over a distributed storage system where $M$ records are stored across $N$ servers by using an $[N,K]$ MDS code. For simplicity, this problem is usually referred as the coded PIR problem. In 2016, Banawan and Ulukus designed the first capacity-achieving coded PIR scheme with sub-Packetization $KN^{M}$ and access number $MKN^{M}$, where capacity characterizes the minimal download size for retrieving per unit of data, and sub-Packetization and access number are two metrics closely related to implementation complexity.In this paper, we focus on minimizing the sub-Packetization and the access number for linear capacity-achieving coded PIR schemes. We first determine the lower bounds on sub-Packetization and access number, which are $Kn^{M-1}$ and $MKn^{M-1}$, respectively, in the nontrivial cases (i.e., $N\!>\!K\!\geq\!1$ and $M\!>\!1$), where $n\!=\!N/{\rm~gcd}(N,K)$. We then design a general linear capacity-achieving coded PIR scheme to simultaneously attain these two bounds, implying tightness of both bounds.
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Building Capacity-Achieving PIR Schemes with Optimal Sub-Packetization over Small Fields
2018 IEEE International Symposium on Information Theory (ISIT), 2018Co-Authors: Jingke Xu, Zhifang ZhangAbstract:Consider N servers with replicated databases containing M records. Suppose a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to T servers. A scheme designed for this purpose is called a T -private information retrieval ( T -PIR) scheme. Three indexes are concerned for PIR schemes: (1) rate, indicating the amount of retrieved information per unit of downloaded data. The highest achievable rate is characterized by the capacity; (2) sub-Packetization, reflecting the implementation complexity for linear schemes; (3) field size. We consider linear schemes over a finite field. In this paper, a general T - PIR scheme simultaneously attaining the optimality of almost all of the three indexes is presented. Specifically, we design a linear capacity-achieving T-PIR scheme with sub-Packetization dnM-1 over a finite field \mathbbFq, q ≥ N. The sub-Packetization dnM-1, where d=gcd(N, T) and n=N/d, has been proved to be optimal in our previous work. The field size is reduced by an exponential factor in our scheme comparing with existing capacity -achieving T - PIR schemes.
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building capacity achieving pir schemes with optimal sub Packetization over small fields
International Symposium on Information Theory, 2018Co-Authors: Jingke Xu, Zhifang ZhangAbstract:Consider $N$ servers with replicated databases containing $M$ records. Suppose a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a $T$ -private information retrieval ( $T$ -PIR) scheme. Three indexes are concerned for PIR schemes: (1) rate, indicating the amount of retrieved information per unit of downloaded data. The highest achievable rate is characterized by the capacity; (2) sub-Packetization, reflecting the implementation complexity for linear schemes; (3) field size. We consider linear schemes over a finite field. In this paper, a general $T$ - PIR scheme simultaneously attaining the optimality of almost all of the three indexes is presented. Specifically, we design a linear capacity-achieving T-PIR scheme with sub-Packetization $dn^{M-1}$ over a finite field $\mathbb{F}_{q}, q\geq N$ . The sub-Packetization $dn^{M-1}$ , where $d=\mathrm{gcd}(N,\ T)$ and $n=N/d$ , has been proved to be optimal in our previous work. The field size is reduced by an exponential factor in our scheme comparing with existing capacity -achieving $T$ - PIR schemes.
Zhifang Zhang - One of the best experts on this subject based on the ideXlab platform.
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the optimal sub Packetization of linear capacity achieving pir schemes with colluding servers
IEEE Transactions on Information Theory, 2019Co-Authors: Zhifang Zhang, Jingke XuAbstract:Suppose $M$ records are replicated in $N$ servers (each storing all $M$ records), a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a $T$ -private information retrieval (PIR) scheme. In practice, capacity-achieving and small sub-Packetization are both desired for PIR schemes, because the former implies the highest download rate and the latter means simple realization. Meanwhile, sub-Packetization is the key technique for achieving capacity. In this paper, we characterize the optimal sub-Packetization for linear capacity-achieving $T$ -PIR schemes. First, a lower bound on the sub-Packetization $L$ for linear capacity-achieving $T$ -PIR schemes is proved, i.e., $L\geq dn^{M-1}$ , where $d={\mathrm{ gcd}}(N,T)$ and $n=N/d$ . Then, for general values of $M$ and $N>T\geq 1$ , a linear capacity-achieving $T$ -PIR scheme with sub-Packetization $dn^{M-1}$ is designed. Comparing with the first capacity-achieving $T$ -PIR scheme given by Sun and Jafar in 2016, our scheme reduces the sub-Packetization from $N^{M}$ to the optimal and further reduces the field size by a factor of $Nd^{M-2}$ .
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The Optimal Sub-Packetization of Linear Capacity-Achieving PIR Schemes With Colluding Servers
IEEE Transactions on Information Theory, 2019Co-Authors: Zhifang Zhang, Jingke XuAbstract:Suppose M records are replicated in N servers (each storing all M records), a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to T servers. A scheme designed for this purpose is called a T-private information retrieval (PIR) scheme. In practice, capacity-achieving and small sub-Packetization are both desired for PIR schemes, because the former implies the highest download rate and the latter means simple realization. Meanwhile, sub-Packetization is the key technique for achieving capacity. In this paper, we characterize the optimal sub-Packetization for linear capacity-achieving T-PIR schemes. First, a lower bound on the sub-Packetization L for linear capacity-achieving T-PIR schemes is proved, i.e., L ≥ dnM-1, where d = gcd(N, T) and n = N/d. Then, for general values of M and N > T ≥ 1, a linear capacity-achieving T-PIR scheme with sub-Packetization dnM-1 is designed. Comparing with the first capacity-achieving T-PIR scheme given by Sun and Jafar in 2016, our scheme reduces the sub-Packetization from NM to the optimal and further reduces the field size by a factor of NdM-2.
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on sub Packetization and access number of capacity achieving pir schemes for mds coded non colluding servers
Science in China Series F: Information Sciences, 2018Co-Authors: Jingke Xu, Zhifang ZhangAbstract:Consider the problem of private information retrieval (PIR) over a distributed storage system where $M$ records are stored across $N$ servers by using an $[N,K]$ MDS code. For simplicity, this problem is usually referred as the coded PIR problem. In 2016, Banawan and Ulukus designed the first capacity-achieving coded PIR scheme with sub-Packetization $KN^{M}$ and access number $MKN^{M}$, where capacity characterizes the minimal download size for retrieving per unit of data, and sub-Packetization and access number are two metrics closely related to implementation complexity.In this paper, we focus on minimizing the sub-Packetization and the access number for linear capacity-achieving coded PIR schemes. We first determine the lower bounds on sub-Packetization and access number, which are $Kn^{M-1}$ and $MKn^{M-1}$, respectively, in the nontrivial cases (i.e., $N\!>\!K\!\geq\!1$ and $M\!>\!1$), where $n\!=\!N/{\rm~gcd}(N,K)$. We then design a general linear capacity-achieving coded PIR scheme to simultaneously attain these two bounds, implying tightness of both bounds.
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Building Capacity-Achieving PIR Schemes with Optimal Sub-Packetization over Small Fields
2018 IEEE International Symposium on Information Theory (ISIT), 2018Co-Authors: Jingke Xu, Zhifang ZhangAbstract:Consider N servers with replicated databases containing M records. Suppose a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to T servers. A scheme designed for this purpose is called a T -private information retrieval ( T -PIR) scheme. Three indexes are concerned for PIR schemes: (1) rate, indicating the amount of retrieved information per unit of downloaded data. The highest achievable rate is characterized by the capacity; (2) sub-Packetization, reflecting the implementation complexity for linear schemes; (3) field size. We consider linear schemes over a finite field. In this paper, a general T - PIR scheme simultaneously attaining the optimality of almost all of the three indexes is presented. Specifically, we design a linear capacity-achieving T-PIR scheme with sub-Packetization dnM-1 over a finite field \mathbbFq, q ≥ N. The sub-Packetization dnM-1, where d=gcd(N, T) and n=N/d, has been proved to be optimal in our previous work. The field size is reduced by an exponential factor in our scheme comparing with existing capacity -achieving T - PIR schemes.
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building capacity achieving pir schemes with optimal sub Packetization over small fields
International Symposium on Information Theory, 2018Co-Authors: Jingke Xu, Zhifang ZhangAbstract:Consider $N$ servers with replicated databases containing $M$ records. Suppose a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a $T$ -private information retrieval ( $T$ -PIR) scheme. Three indexes are concerned for PIR schemes: (1) rate, indicating the amount of retrieved information per unit of downloaded data. The highest achievable rate is characterized by the capacity; (2) sub-Packetization, reflecting the implementation complexity for linear schemes; (3) field size. We consider linear schemes over a finite field. In this paper, a general $T$ - PIR scheme simultaneously attaining the optimality of almost all of the three indexes is presented. Specifically, we design a linear capacity-achieving T-PIR scheme with sub-Packetization $dn^{M-1}$ over a finite field $\mathbb{F}_{q}, q\geq N$ . The sub-Packetization $dn^{M-1}$ , where $d=\mathrm{gcd}(N,\ T)$ and $n=N/d$ , has been proved to be optimal in our previous work. The field size is reduced by an exponential factor in our scheme comparing with existing capacity -achieving $T$ - PIR schemes.
Venkatesan Guruswami - One of the best experts on this subject based on the ideXlab platform.
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Near-optimal Repair of Reed-Solomon Codes with Low Sub-Packetization
2019 IEEE International Symposium on Information Theory (ISIT), 2019Co-Authors: Venkatesan Guruswami, Haotian JiangAbstract:Minimum storage regenerating (MSR) codes are MDS codes which allow for recovery of any single erased symbol with optimal repair bandwidth, based on the smallest possible fraction of the contents downloaded from each of the other symbols. Recently, certain Reed- Solomon codes were constructed which are MSR. However, the sub-Packetization of these codes is exponentially large, growing like nΩ(n) in the constant-rate regime. In this work, we study the relaxed notion of ϵ-MSR codes, which incur a factor of (1 + ϵ) higher than the optimal repair bandwidth, in the context of Reed-Solomon codes. We give constructions of constant-rate ϵ-MSR Reed-Solomon codes with polynomial sub-Packetization of nO(l/ϵ) and thereby giving an explicit tradeoff between the repair bandwidth and sub-Packetization.
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near optimal repair of reed solomon codes with low sub Packetization
arXiv: Data Structures and Algorithms, 2019Co-Authors: Venkatesan Guruswami, Haotian JiangAbstract:Minimum storage regenerating (MSR) codes are MDS codes which allow for recovery of any single erased symbol with optimal repair bandwidth, based on the smallest possible fraction of the contents downloaded from each of the other symbols. Recently, certain Reed-Solomon codes were constructed which are MSR. However, the sub-Packetization of these codes is exponentially large, growing like $n^{\Omega(n)}$ in the constant-rate regime. In this work, we study the relaxed notion of $\epsilon$-MSR codes, which incur a factor of $(1+\epsilon)$ higher than the optimal repair bandwidth, in the context of Reed-Solomon codes. We give constructions of constant-rate $\epsilon$-MSR Reed-Solomon codes with polynomial sub-Packetization of $n^{O(1/\epsilon)}$ and thereby giving an explicit tradeoff between the repair bandwidth and sub-Packetization.
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an exponential lower bound on the sub Packetization of msr codes
Symposium on the Theory of Computing, 2019Co-Authors: Omar Alrabiah, Venkatesan GuruswamiAbstract:An (n,k,l)-vector MDS code is a F-linear subspace of (Fl)n (for some field F) of dimension kl, such that any k (vector) symbols of the codeword suffice to determine the remaining r=n−k (vector) symbols. The length l of each codeword symbol is called the Sub-Packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading l/r field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large Sub-Packetization l ≳ rk/r. Our main result is an almost tight lower bound showing that for an MSR code, one must have l ≥ exp(Ω(k/r)). Previously, a lower bound of ≈ exp(√k/r), and a tight lower bound for a restricted class of ”optimal access” MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one key definition that is somewhat inspired by Galois theory.
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an exponential lower bound on the sub Packetization of msr codes
arXiv: Information Theory, 2019Co-Authors: Omar Alrabiah, Venkatesan GuruswamiAbstract:An $(n,k,\ell)$-vector MDS code is a $\mathbb{F}$-linear subspace of $(\mathbb{F}^\ell)^n$ (for some field $\mathbb{F}$) of dimension $k\ell$, such that any $k$ (vector) symbols of the codeword suffice to determine the remaining $r=n-k$ (vector) symbols. The length $\ell$ of each codeword symbol is called the sub-Packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading $\ell/r$ field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large sub-Packetization $\ell \gtrsim r^{k/r}$. Our main result is an almost tight lower bound showing that for an MSR code, one must have $\ell \ge \exp(\Omega(k/r))$. Previously, a lower bound of $\approx \exp(\sqrt{k/r})$, and a tight lower bound for a restricted class of "optimal access" MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one key definition that is somewhat inspired by Galois theory.
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mds code constructions with small sub Packetization and near optimal repair bandwidth
arXiv: Information Theory, 2017Co-Authors: Ankit Singh Rawat, Itzhak Tamo, Venkatesan Guruswami, Klim EfremenkoAbstract:This paper addresses the problem of constructing MDS codes that enable exact repair of each code block with small repair bandwidth, which refers to the total amount of information flow from the remaining code blocks during the repair process. This problem naturally arises in the context of distributed storage systems as the node repair problem [7]. The constructions of exact-repairable MDS codes with optimal repair-bandwidth require working with large sub-Packetization levels, which restricts their employment in practice. This paper presents constructions for MDS codes that simultaneously provide both small repair bandwidth and small sub-Packetization level. In particular, this paper presents two general approaches to construct exact-repairable MDS codes that aim at significantly reducing the required sub-Packetization level at the cost of slightly sub-optimal repair bandwidth. The first approach gives MDS codes that have repair bandwidth at most twice the optimal repair-bandwidth. Additionally, these codes also have the smallest possible sub-Packetization level $\ell = O(r)$, where $r$ denotes the number of parity blocks. This approach is then generalized to design codes that have their repair bandwidth approaching the optimal repair-bandwidth at the cost of graceful increment in the required sub-Packetization level. The second approach transforms an MDS code with optimal repair-bandwidth and large sub-Packetization level into a longer MDS code with small sub-Packetization level and near-optimal repair bandwidth. For a given $r$, the obtained codes have their sub-Packetization level scaling logarithmically with the code length. In addition, the obtained codes require field size only linear in the code length and ensure load balancing among the intact code blocks in terms of the information downloaded from these blocks during the exact reconstruction of a code block.
Pascal Bouvry - One of the best experts on this subject based on the ideXlab platform.
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Effect of Packetization interval on number of connections in AAC audio streaming over WLAN 802.11g
The 17th Asia Pacific Conference on Communications, 2011Co-Authors: K. Lavangnananda, C. Angsuchotmetee, Pascal BouvryAbstract:Audio streaming over wireless local area network (WLAN) has an ability to transmit audio data ranging from short messages to music station. A popular application of this is in setting up a community radio, which is in demand, especially in developing countries where frequency spectrum management is still problematic. Audio streaming has to assure high quality of content reception without any packet loss, if possible. One such suitable coder-decoder (CODEC) is the Advanced Audio Coding (AAC). Packetization interval for audio streaming is usually set at a default value of 20 ms. This work develops an AAC Audio Streaming over WLAN 802.11g. It studies the effect of different Packetization intervals has on the maximum number of possible connections (i.e. receivers) without any packet loss. The simulated environment comprises of 1 access point with 300 m2. Connecting media server to access point via wireless link is adopted for its mobility and ease of deployment in rural area. The range of Packetization intervals under this study is from 20 ms. to 200 ms. The study reveals that the commonly use default value of 20 ms. can manage up to 13 connections. Under the scenario of this study, it was found that the best Packetization interval is 70 ms. with the maximum of 33 connections. The study also reveals that packet delay is not an issue in this approach as all are under the acceptable standard of 400 ms.
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Suitable Packetization interval for using Constrained Energy Lapped Transform (CELT) CODEC in Bi-directional communication over WLAN 802.11g
The 17th Asia Pacific Conference on Communications, 2011Co-Authors: K. Lavangnananda, K. Yongsakun, Pascal BouvryAbstract:Full audio bandwidth with very low algorithmic delay CODEC is state-of-the-art in CODEC technology. This type of CODEC is expected to support full frequency range for human hearing. It will enable future multipurpose audio applications, especially those which require high quality of audio signal with very low delay. A popular choice for this type of CODEC is the Constrained Energy Lapped Transform (CELT) CODEC since it is an open source and royalty free. This study is concerned with the effect of Packetization interval for using CELT CODEC in bidirectional communication over WLAN 802.11g with respect to packet loss and end-to-end delay. Possible bitrates used in CELT were also investigated. The result reveals that the commonly default 20 ms. Packetization interval is not always suitable for all network conditions. High Packetization interval (more than 60 ms) interval are not recommended as packet loss can be quite high and end-to-end delay can exceed the 150 ms. ITU recommended value. Using Packetization interval at 30 ms. is recommended, apart from achieving better performance, it allows CODEC bitrate to be varied while packet loss is still acceptable and end-to-end delay is still within the recommended value. A practical application for this study is a synchronous remote music session practice between two persons.
