network coding is a reasonable way to increase network efficiency in response to an increase of sensed data in the Internet of Things (IoT). In network coding, intermediate nodes combine packets received from neighbor...
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network coding is a reasonable way to increase network efficiency in response to an increase of sensed data in the Internet of Things (IoT). In network coding, intermediate nodes combine packets received from neighboring nodes, transform, and transmit encoded packets that can be decoded at the destination. This scheme is based on trust among nodes. If any malicious node joins the network, it can act as an intermediate node that could fabricate encoded packets. It might be more difficult to identify the authenticity of such encoded packets since packets that are received at the destination might not originate from a single source, but be combined with several other packets originating from multiple sources. In this paper, we propose a scheme on how to detect attacked packets among the received packets at a destination and how to recover the original message from the packets including the attacked "look-like-valid" packets. This scheme shows that a destination could recover the valid message with just the received packets including some attacked packets and will result in a quite efficient performance in network coding.
By extending the traditional store-and-forward mechanism, network coding has the capability to improve a network's throughput, robustness, and security. Given the fundamentally different packet processing required...
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ISBN:
(纸本)9781728143873
By extending the traditional store-and-forward mechanism, network coding has the capability to improve a network's throughput, robustness, and security. Given the fundamentally different packet processing required by this new paradigm and the inflexibility of hardware, existing solutions are based on software. As a result, they have limited performance and scalability, creating a barrier to its wide-spread adoption. By leveraging the recent advances in programmable networking hardware, in this paper we propose a random linear network coding data plane written in P4, as a first step towards a production-level platform. Our solution includes the ability to combine the payload of multiple packets and of executing the required Galois field operations, and shows promise to be practical even under the strict memory and processing constraints of switching hardware.
For energy conservation in a wireless sensor network (WSN), in our previous work [V. Ho, I. Nikolaidis, ADHOC-NOW 2015: p. 48-61], we introduce a TDMA schedule construction technique for arbitrary topology networks wh...
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ISBN:
(纸本)9781728150093
For energy conservation in a wireless sensor network (WSN), in our previous work [V. Ho, I. Nikolaidis, ADHOC-NOW 2015: p. 48-61], we introduce a TDMA schedule construction technique for arbitrary topology networks whose nodes duty cycle (DC) in a periodic fashion. In our other work [V. Ho, I. Nikolaidis, ACOMP 2017: p. 28-35], we present the modeling of XOR-pairwise network coding (NC) for duty-cycled WSNs to figure out per-flow rates by the optimization step resulted from the max-min fairness formulation used with the max-min programming algorithm. With the values of optimized per-flow rates used by the original TDMA schedule construction technique, in this paper, we propose the NC-based TDMA schedule construction technique to produce an improved TDMA schedule of all the nodes in the network. Numerous simulation studies show the new technique can greatly improve the total throughput that are reduced by switching nodes (transceivers) OFF.
Batched network coding is a variation of random linear network coding which has low computational and storage costs. In order to adapt random fluctuations in the number of erasures in individual batches, it is not opt...
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ISBN:
(纸本)9781538692912
Batched network coding is a variation of random linear network coding which has low computational and storage costs. In order to adapt random fluctuations in the number of erasures in individual batches, it is not optimal to recode and transmit the same number of packets for all batches. Different distributed optimization problems, which are called adaptive recoding, were formulated for this purpose. The key component of these optimization problems is the expected value of the rank distribution of a batch at the next network node, which also known as the expected rank. In this paper, we put forth a unified adaptive recoding framework. We show that the expected rank functions are concave when the packet loss pattern follows a stationary stochastic process regardless of the field size, which covers but not limited to independent packet loss and burst packet loss. Under this concavity property, we show that there always exists a preferred solution which not only can make the number of recoded packets almost deterministic but can also tolerate rank distribution errors due to inaccurate measurements or limited precision of the machine. To obtain such an optimal solution, we propose tuning schemes that can turn any feasible solution into one with the above desired properties.
The last decade has witnessed a rising interest in Gossip protocols in distributed systems. In particular, as soon as there is a need to disseminate events, they become a key functional building block due to their sca...
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ISBN:
(纸本)9781728105154
The last decade has witnessed a rising interest in Gossip protocols in distributed systems. In particular, as soon as there is a need to disseminate events, they become a key functional building block due to their scalability, robustness and fault tolerance under high churn. However, Gossip protocols are known to be bandwidth intensive. A huge amount of algorithms has been studied to limit the number of exchanged messages using different combinations of push/pull approaches. We are revisiting the state of the art by applying Random Linear network coding to further increase performance. In particular, the originality of our approach is to combine sparse-vector encoding to send our network-coding coefficients and Lamport timestamps to split messages in generations in order to provide an efficient gossiping. Our results demonstrate that we are able to drastically reduce bandwidth overhead and dissemination delay compared to the state of the art.
Transmission Control Protocol with network coding (TCP/NC) has been a potential proposal to improve the transmission performance of TCP in lossy networks while it still takes advantage of congestion and retransmission...
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ISBN:
(纸本)9781728105253
Transmission Control Protocol with network coding (TCP/NC) has been a potential proposal to improve the transmission performance of TCP in lossy networks while it still takes advantage of congestion and retransmission control of TCP for reliable end-to-end data transfer. TCP/NC uses additional sub-layer called network coding layer below the TCP layer to handle packet losses without sensed by the TCP layer. In our previous work, we introduced some variants of TCP/NC such as TCP/NCwLRLBE (TCP/NC with Loss Rate and Loss Burstiness Estimation) which can improve the retransmission and adapt to the changing of the channel. However, it is just evaluated on the simple packet loss conditions, e.g., random loss or Gilbert loss. On the other hand, reliable end-to-end data transfer in diverse IoT (Internet of Things) environments (e.g., Power Line Communication - PLC) in a cost-efficient manner is an emerging challenge. Therefore, in this paper, we investigate the characteristics of the TCP/NC on PLC networks, to have a more in-depth evaluation of its performance and applicability in a practical PLC environment with many conditions causing packet loss such as noise variants, distance, etc. The result of our simulation on ns-3 (network Simulation 3) shows that TCP/NC can work well on PLC environment compared to the traditional protocols such as TCP NewReno with Selective Acknowledgment (SACK) and TCP Westwood+.
In this paper we introduce our network coding Module (NCM) for bidirectional random linear network coding in wireless networks. It is based on our low-level frame injection library libmoep, which allows to easily impl...
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ISBN:
(纸本)9781728105680
In this paper we introduce our network coding Module (NCM) for bidirectional random linear network coding in wireless networks. It is based on our low-level frame injection library libmoep, which allows to easily implement custom link-layer protocols. Originally intended for IEEE 802.11 only, it meanwhile also supports wired Ethernet-based networks. We evaluate the NCM in a wireless testbed with and without relay. For both cases we derive optimal packet injection rates and perform tests with TCP. The source code of this paper is made available for download under the GPLv2 at [1].
In most of the network coding problems with k messages, the existence of binary network coding solution over F-2 depends on the existence of adequate sets of k-dimensional binary vectors such that each set comprises o...
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ISBN:
(纸本)9781538692912
In most of the network coding problems with k messages, the existence of binary network coding solution over F-2 depends on the existence of adequate sets of k-dimensional binary vectors such that each set comprises of linearly independent vectors. In a given k x n (n >= k) binary matrix, there exist ((n))(k) binary sub-matrices of size k x k. Every possible k x k sub-matrix may be of full rank or singular depending on the columns present in the matrix. In this work, for full rank binary matrix G of size k x n satisfying certain condition on minimum Hamming weight, we establish a relation between the number of full rank sub-matrices of size k x k and the weight enumerating function of the error correcting code with G as the generator matrix. We give an algorithm to compute the number of full rank k x k submatrices.
For classic wireless sensor networks (WSN), the received data is only stored and forwarded by nodes [1]. Existing research has shown that network coding can make the nodes form a store-encode-forward mode, which is a ...
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ISBN:
(纸本)9781728162973
For classic wireless sensor networks (WSN), the received data is only stored and forwarded by nodes [1]. Existing research has shown that network coding can make the nodes form a store-encode-forward mode, which is a great improvement on the performance of wireless sensor networks. According to the above analysis, this paper chooses the SPIN protocol as our research object and looks for opportunities to use the network coding in the SPIN protocol when the intermediate node broadcasts the ADV message [2]. On this basis, this paper proposes a new improved routing protocol NC-SPIN based on network coding. Through simulation experiments, it can be found that the NC-SPIN routing protocol has improved throughput and communication performance and decreased energy consumption at intermediate nodes compared to the SPIN protocol.
Sorting extremely large datasets is a frequently occuring task in practice. These datasets are usually much larger than the computer's main memory;thus external memory sorting algorithms, first introduced by Aggar...
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ISBN:
(纸本)9781450367059
Sorting extremely large datasets is a frequently occuring task in practice. These datasets are usually much larger than the computer's main memory;thus external memory sorting algorithms, first introduced by Aggarwal and Vitter (1988), are often used. The complexity of comparison based external memory sorting has been understood for decades by now, however the situation remains elusive if we assume the keys to be sorted are integers. In internal memory, one can sort a set of n integer keys of Theta(lg n) bits each in O(n) time using the classic Radix Sort algorithm, however in external memory, there are no faster integer sorting algorithms known than the simple comparison based ones. Whether such algorithms exist has remained a central open problem in external memory algorithms for more than three decades. In this paper, we present a tight conditional lower bound on the complexity of external memory sorting of integers. Our lower bound is based on a famous conjecture in network coding by Li and Li (2004), who conjectured that network coding cannot help anything beyond the standard multicommodity flow rate in undirected graphs. The only previous work connecting the Li and Li conjecture to lower bounds for algorithms is due to Adler et al. (2006). Adler et al. indeed obtain relatively simple lower bounds for oblivious algorithms (the memory access pattern is fixed and independent of the input data). Unfortunately obliviousness is a strong limitations, especially for integer sorting: we show that the Li and Li conjecture implies an Omega(n lg n) lower bound for internal memory oblivious sorting when the keys are Theta(lg n) bits. This is in sharp contrast to the classic (non-oblivious) Radix Sort algorithm. Indeed going beyond obliviousness is highly non-trivial;we need to introduce several new methods and involved techniques, which are of their own interest, to obtain our tight lower bound for external memory integer sorting.
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