Yunlong Zhao, Shilong Kang, Masayuki Iwai et al. · 2012
Network coding has been considered as an effective approach to improve the wireless network throughput. However, due to the unreliability of wireless links and the loss of transmission, the decoded node sometimes cannot receive enough native packets to succeed in decoding. So how to recovery decoding failure is a key issue, which is considered as the "coding recovery" problem and has become a hot spot. In this paper, a novel coding recovery scheme is proposed, named as CBCR (Coding-Based Coding Recovery), which makes use of the network coding method to encoded the lost native packets, then retransmit them to the decoded node to help it recovery such decoding failure problem. The experiment is well done on the wireless networks prototype system with several Sun SPOTs, and the results show that CBCR is a promising candidate for coding recovery, and its efficiency and performance are superior to the conventional recovery schemes.
Cited by 0
Anthony Ephremides, Sidharth Jaggi, Tracey Ho et al. · Journal of Communications and Networks · 2008
In less than ten years Network Coding has grown from a simple cute idea to an almost revolutionary research trend that has galvanized both the Information-theoretic Community (where it was born) and the Networking Community (where it is expected to find its applications). By now, a casual observer might mistakenly conclude that the story of Network Coding is complete, that its fundamental properties are well understood, the challenges and obstacles have been identified, and that only limited applications of it have found their way to practice. This issue is proof to the contrary; that is, there is ample room for further theoretical development and there is a truly endless list of potential applications.
Cited by 1
Lehman, April Rasala, 1977- · DSpace@MIT (Massachusetts Institute of Technology) · 2006
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Cited by 0Open access
Ad Hoc Ne · 2010
Cited by 0
Juan A. Cabrera, Morten V. Pedersen, Frank H. P. Fitzek · Elsevier eBooks · 2020
Cited by 1
Mohammad A. Matin · Directory of Open access Books (OAPEN Foundation) · 2018
Network coding is an elegant and novel technique that allows nodes in the network to perform coding operations at the packet level. In particular, network coding represents a powerful approach to protect data from losses due to link disconnections and can also exploit the combination of multiple links to deliver data to users with the possibility of recoding at intermediate nodes. This phenomenon will reduce information congestion at some nodes or links, which will improve the network information flow such as to increase network throughput and robustness. This book is intended to provide the current R&D trends in coding, detection, and signal processing applied to communications in wireless and wired networks.
Cited by 0Open access
April Rasala Lehman · 2005
Cited by 0
April Rasala Lehman, Madhu Sudan · 2005
In the network coding problem, there are k commodities each with an associated message Mi, a set of sources that know Mi and a set of sinks that request Mi. Each edge in the graph may transmit any function of the messages. These functions define a network coding solution.
We explore three topics related to network coding. First, for a model in which the messages and the symbols transmitted on edges are all from the same alphabet Σ, we prove lower bounds on |Σ|. In one case, we prove |Σ| needs to be doubly-exponential in the size of the network. We also show that it is NP-hard to determine the smallest alphabet size admitting a solution.
We then explore the types of functions that admit solutions. In a linear solution over a finite field F the symbol transmitted over each edge is a linear combination of the messages. We show that determining if there exists a linear solution is NP-hard for many classes of network coding problems. As a corollary, we obtain a solvable instance of the network coding problem that does not admit a linear solution over any field F .
We then define a model of network coding in which messages are chosen from one alphabet, Γ, and edges transmit symbols from another alphabet, Σ. In this model, we define the rate of a solution as log |Γ|/log |Σ|. We then explore techniques to upper bound the maximum achievable rate for instances defined on directed and undirected graphs. We present a network coding instance in an undirected graph in which the maximum achievable rate is strictly smaller than the sparsity of the graph. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Cited by 33
Lehman, April Rasala, 1977- · DSpace@MIT (Massachusetts Institute of Technology) · 2005
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Cited by 0Open access
Al Agha, Khaldoun · 2012
Cited by 0
Christina Fragouli, Jean‐Yves Le Boudec, Joerg Widmer · ACM SIGCOMM Computer Communication Review · 2006
Network coding is a new research area that may have interesting applications in practical networking systems. With network coding, intermediate nodes may send out packets that are linear combinations of previously received information. There are two main benefits of this approach: potential throughput improvements and a high degree of robustness. Robustness translates into loss resilience and facilitates the design of simple distributed algorithms that perform well, even if decisions are based only on partial information. This paper is an instant primer on network coding: we explain what network coding does and how it does it. We also discuss the implications of theoretical results on network coding for realistic settings and show how network coding can be used in practice
Cited by 749Open access
Sanjay Srivastava, Conventional Unicast, Zunnun Narmawala et al. · 2007
Cited by 0
Ephremides, Anthony, Jaggi, Sidharth, Ho, Tracey et al. · CaltechAUTHORS (California Institute of Technology) · 2008
In less than ten years Network Coding has grown from a simple cute idea to an almost revolutionary research trend that has galvanized both the Information-theoretic Community (where it was born) and the Networking Community (where it is expected to find its applications). By now, a casual observer might mistakenly conclude that the story of Network Coding is complete, that its fundamental properties are well understood, the challenges and obstacles have been identified; that is, there is ample room for further theoretical development and there is a truly endless list of potential applications. \n \n \n
Cited by 0
Tracey Ho, Desmond S. Lun · Cambridge University Press eBooks · 2008
Network coding promises to significantly impact the way communications networks are designed, operated, and understood. This book presents a unified and intuitive overview of the theory, applications, challenges, and future directions of this emerging field, and is a must-have resource for those working in wireline or wireless networking. • Uses an engineering approach - explains the ideas and practical techniques • Covers mathematical underpinnings, practical algorithms, code selection, security, and network management • Discusses key topics of inter-session (non-multicast) network coding, lossy networks, lossless networks, and subgraph-selection algorithms Starting with basic concepts, models, and theory, then covering a core subset of results with full proofs, Ho and Lun provide an authoritative introduction to network coding that supplies both the background to support research and the practical considerations for designing coded networks. This is an essential resource for graduate students and researchers in electronic and computer engineering and for practitioners in the communications industry.
Cited by 239
Michael Langberg · Open Collections · 2014
Cited by 0Open access
Masahito Hayashi · Entropy · 2021
When a network has relay nodes, there is a risk that a part of the information is leaked to an untrusted relay. Secure network coding (secure NC) is known as a method to resolve this problem, which enables the secrecy of the message when the message is transmitted over a noiseless network and a part of the edges or a part of the intermediate (untrusted) nodes are eavesdropped. If the channels on the network are noisy, the error correction is applied to noisy channels before the application of secure NC on an upper layer. In contrast, secure physical layer network coding (secure PLNC) is a method to securely transmit a message by a combination of coding operation on nodes when the network is composed of set of noisy channels. Since secure NC is a protocol on an upper layer, secure PLNC can be considered as a cross-layer protocol. In this paper, we compare secure PLNC with a simple combination of secure NC and error correction over several typical network models studied in secure NC.
Cited by 6Open access
Masahito Hayashi · 2018
Secure network coding realizes the secrecy of the message when the message is transmitted via noiseless network and a part of edges or a part of intermediate nodes are eavesdropped. In this framework, if the channels of the network has noise, we apply the error correction to noisy channel before applying the secure network coding. In contrast, secure physical layer network coding is a method to securely transmit a message by a combination of coding operation on nodes when the network is given as a set of noisy channels. In this paper, we give several examples of network, in which, secure physical layer network coding realizes a performance that cannot be realized by secure network coding.
Cited by 8
Masahito Hayashi, et al. · 2006
Since quantum information is continuous, its handling is sometimes surprisingly harder than the classical counterpart. A typical example is cloning; making a copy of digital information is straightforward but it is not possible exactly for quantum information. The question in this paper is whether or not quantum network coding is possible. Its classical counterpart is another good example to show that digital information flow can be done much more efficiently than conventional (say, liquid) flow. Our answer to the question is similar to the case of cloning, namely, it is shown that quantum network coding is possible if approximation is allowed, by using a simple network model called Butterfly. In this network, there are two flow paths, s1 to t1 and s2 to t2, which shares a single bottleneck channel of capacity one. In the classical case, we can send two bits simultaneously, one for each path, in spite of the bottleneck. Our results for quantum network coding include: (i) We can send any quantum state |ψ1 〉 from s1 to t1 and |ψ2 〉 from s2 to t2 simultaneously with a fidelity strictly greater than 1/2. (ii) If one of |ψ1 〉 and |ψ2 〉 is classical, then the fidelity can be improved to 2/3. (iii) Similar improvement is also possible if |ψ1 〉 and |ψ2 〉 are restricted to only a finite number of (previously known) states. This allows us to design an interesting protocol which can send two classical bits from s1 to t1 (similarly from s2 to t2) but only one of them should be recovered.
Cited by 0
Zongpeng Li, Xunrui Yin, Xin Wang et al. · 2011
Cited by 0
Marie‐José Montpetit, Vincent Roca, Jonathan Detchart et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2015
HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Cited by 0Open access