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An one-time pad cryptographic algorithm with Huffman source coding based energy aware sensor node design

SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 2024年 44卷

作者： Saravanaselvan, A. Paramasivan, B. Natl Engn Coll Dept Elect & Commun Engn Kovilpatti Tamil Nadu India Natl Engn Coll Dept Informat Technol Kovilpatti Tamil Nadu India

Recently, the security-based algorithms for energy-constrained sensor nodes are being developed to consume less energy for computation as well as communication. For the mission critical wireless sensor network (WSN) applications, continuous and secure data collection from WSN nodes is an essential task on the deployed field. Therefore, in this manuscript, One-Time Pad Cryptographic Algorithm with Huffman source coding Based Energy Aware sensor node Design is proposed (EA-SND-OTPCA-HSC). Before transmission, the distance among transmitter and receiver is rated available in mission critical WSN for lessen communication energy consume of sensor node. For the mission critical WSN applications, continuous and secure data collection from WSN nodes is an essential task on the deployed field. The periodic sleep/wake up scheme with Huffman source coding algorithm is used to save energy at the node level. Then, one-time pad cryptographic algorithm in each sensor node, the vernam cipher encryption technique is applied to the compact payload. The proposed technique is executed and efficacy of proposed method is assessed using Payload Vs Energy consume for one sensor node, communication energy consume for one sensor node with different distances, energy consume for one sensor node under various methods, Throughput, delay and Jitter are analyzed. Then the proposed method provides 90.12 %, 89.78 % and 91.78 % lower delay and 88.25 %, 95.34 % and 94.12 % lesser energy consumption comparing to the existing EA-SND-Hyb-MG-CUF, EA-SND-PVEH and EA-SND-PIA techniques respectively.

关键词： Cryptography Energy consumption Information security One-time pad with Huffman source coding source coding Wireless sensor network

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MULTIPLE DESCRIPTION source-coding WITH NO EXCESS MARGINAL RATE

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IEEE TRANSACTIONS ON INFORMATION THEORY 1995年第2期41卷 349-357页

作者： ZHANG, Z BERGER, T CORNELL UNIV SCH ELECT ENGN ITHACA NY 14853 USA

Multiple description source coding concerns situations in which the transmission of the source information is distributed over two data streams at rates R(1) and R(2), respectively. When both data streams are received, the decoder uses the combined data at rate R(1) + R(2) to reconstruct the source information with average distortion d(0). If a communication breakdown prevents one of the data streams from reaching the receiver, the decoder has to base its reconstruction solely on the available data at rate either R(1) or R(2). This results in a higher distortion of either d(1) or d(2), respectively. The region R of all achievable quintuples (R(1), R(2), d(0), d(1), d(2)) has been determined in the so-called ''no excess rate'' sum case defined by imposing the requirement R(1) + R(2) = R(d(0)), where R(.) is the rate-distortion function of the source. The case with excess rate sum, characterized by R(1) + R(2) > R(d(0)), is challenging. We study in this paper a special case of it in which the requirements R(t) = R(d(t)), t = 1, 2, are imposed;we refer to this as the ''no excess marginal rate'' case. The lower and upper bounds on d(0) we obtain are separated by only a tiny gap when evaluated for a binary equiprobable source and the Hamming distortion measure.

关键词： MULTIPLE DESCRIPTION source coding EXCESS RATE RATE DISTORTION

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Achieving the Optimum Rate for Cross-Modal source coding

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IEEE TRANSACTIONS ON MULTIMEDIA 2024年 26卷 9722-9735页

作者： Yuan, Zhe Wu, Dan Zhou, Liang Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Network Minist Educ Nanjing 210003 Peoples R China Army Engn Univ PLA Coll Commun Engn Nanjing 210007 Peoples R China

Multi-modal applications are expected to dominate in the 5G and B5G era. However, traditional source coding methods are not efficient or reliable due to neglecting semantic redundancy and mutual influences between different modalities' sources. To address this, cross-modal source coding (CMSC) has been proposed as a promising solution. However, there are still two main challenges: determining the optimum rate of CMSC considering delay and reliability constraints, and designing a practical CMSC near the optimum rate. To tackle these challenges, this paper focuses on studying the optimum source coding rate of CMSC and its practical implementation. On the theoretical side, an (n, epsilon)-achievable rate region is derived, representing the source coding rates subject to a fixed blocklength n and the target error probability e . Additionally, the optimum source coding rate can be approximated by calculating the infimum of the (n, epsilon)- achievable rate region with a rate dispersion function. On the technical side, a general implementation for CMSC is proposed, which fully leveraging channel coding and artificial intelligence (AI) semantic analysis to achieve the optimum rate. Numerical results demonstrate that CMSC can obtain 50% improvement in theory and 37.5% enhancement in practice against the baseline model abstracted from traditional schemes when multi-modal sources are semantically correlated.

关键词： Semantics source coding Haptic interfaces Reliability Streams Redundancy Decoding Cross-modal source coding semantic relevance achievable rate region optimum rate video and haptic coding

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OPTIMAL PRUNING WITH APPLICATIONS TO TREE-STRUCTURED source-coding AND MODELING

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IEEE TRANSACTIONS ON INFORMATION THEORY 1989年第2期35卷 299-315页

作者： CHOU, PA LOOKABAUGH, T GRAY, RM COMPRESS LABS INC SAN JOSE CA 95134 USA STANFORD UNIV DEPT ELECT ENGN INFORMAT SYST LAB STANFORD CA 94305 USA

An algorithm introduced by L. Breiman et al. (1984) in the context of classification and regression trees is reinterpreted and extended to cover a variety of applications in source coding and modeling in which trees are involved. These include variable-rate and minimum-entropy tree-structured vector quantization, minimum expected cost decision trees, variable-order Markov modeling, optimum bit allocation, and computer graphics and image processing using quadtrees. A concentration on the first of these and a detailed analysis of variable-rate tree-structured vector quantization are provided. It is found that variable-rate tree-structured vector quantization outperforms not only the fixed-rate variety but also full-search vector quantization. The successive approximation character of variable-rate tree-structured vector quantization permits it to degrade gracefully if the rate is reduced at the encoder. This has applications to the problem of buffer overflow.

关键词： COMPUTER GRAPHICS classification and regression trees ENCODER Vector quantization source coding Modeling

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On multistage successive refinement for Wyner-Ziv source coding with degraded side informations

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IEEE TRANSACTIONS ON INFORMATION THEORY 2007年第8期53卷 2946-2960页

作者： Tian, Chao Diggavi, Suhas N. Ecole Polytech Fed Lausanne IC ISC LICOS CH-1015 Lausanne Switzerland Ecole Polytech Fed Lausanne LICOS IC Sch Comp & Commun Sci CH-1015 Lausanne Switzerland

In this correspondence, we provide a complete characterization of the rate-distortion region for the multistage successive refinement of the Wyner-Ziv source coding problem with degraded side informations at the decoder. Necessary and sufficient conditions for a source to be successively refinable along a distortion vector are subsequently derived. A source-channel separation theorem is provided when the descriptions are sent over independent channels for the multistage case. Furthermore, the notion of generalized successive refinability with multiple degraded side informations is introduced. This notion captures whether progressive encoding to satisfy multiple distortion constraints for different side informations is as good as encoding without progressive requirement. Necessary and sufficient conditions for generalized successive refinability are given. It is shown that the following two sources are generalized successively refinable: 1) the Gaussian source with degraded Gaussian side informations and 2) the doubly symmetric binary source when the worse side information is a constant. Thus for both cases, the failure of being successively refinable is only due to the inherent uncertainty on which side information will occur at the decoder, but not the progressive encoding requirement.

关键词： degradedness rate distortion side information source coding successive refinement

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Semantic Filtering and source coding in Distributed Wireless Monitoring Systems

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IEEE TRANSACTIONS ON COMMUNICATIONS 2024年第6期72卷 3290-3304页

作者： Agheli, Pouya Pappas, Nikolaos Kountouris, Marios EURECOM Commun Syst Dept F-06904 Sophia Antipolis France Linkoping Univ Dept Comp & Informat Sci S-58183 Linkoping Sweden

The problem of goal-oriented semantic filtering and timely source coding in multiuser communication systems is considered here. We study a distributed monitoring system in which multiple information sources, each observing a physical process, provide status update packets to multiple monitors having heterogeneous goals. Two semantic filtering schemes are first proposed as a means to admit or drop arrival packets based on their goal-dependent importance, which is a function of the intrinsic and extrinsic attributes of information and the probability of occurrence of each realization. Admitted packets at each sensor are then encoded and transmitted over block-fading wireless channels so that served monitors can timely fulfill their goals. A truncated error control scheme is derived, which allows transmitters to drop or retransmit undelivered packets based on their significance. Then, we formulate the timely source encoding optimization problem and analytically derive the optimal codeword lengths assigned to the admitted packets which maximize a weighted sum of semantic utility functions for all pairs of communicating sensors and monitors. Our analytical and numerical results provide the optimal design parameters for different arrival rates and highlight the improvement in timely status update delivery using the proposed semantic filtering, source coding, and error control schemes.

关键词： Semantics Monitoring source coding Transmitters Protocols Error correction Performance evaluation Goal-oriented semantic communication semantic filtering timely source coding distributed monitoring systems

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PYRAMIDAL MULTIRESOLUTION source-coding FOR PROGRESSIVE SEQUENCES

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1994年第4期40卷 789-795页

作者： CANDOTTI, G CARRATO, S FILISAN, AP SICURANZA, GL UNIV TRIESTE DEEII-34127 TRIESTEITALY

A hierarchical video source coding algorithm based on MPEG-2 is presented. The proposed coding scheme is characterized by (i) non-interlaced pictures for each layer;(2) hierarchical motion estimation able to provide physical motion vectors for both ''B'' and ''P'' pictures;(iii) hierarchical spatial scalability-which is the main feature of a system for a multiresolution MPEG-2-like coding architecture-without any increase in the total bit rate. Several alternative solutions are proposed and evaluated.

关键词： source coding Spatial resolution Signal resolution Transform coding Bit rate TV Displays Motion estimation Bandwidth Multimedia communication

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Semisupervised Clustering by Queries and Locally Encodable source coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第2期67卷 1141-1155页

作者： Mazumdar, Arya Pal, Soumyabrata Univ Massachusetts Coll Informat & Comp Sci Amherst MA 01003 USA

source coding is the canonical problem of data compression in information theory. In a locally encodable source coding, each compressed bit depends on only few bits of the input. In this paper, we show that a recently popular model of semisupervised clustering is equivalent to locally encodable source coding. In this model, the task is to perform multiclass labeling of unlabeled elements. At the beginning, we can ask in parallel a set of simple queries to an oracle who provides (possibly erroneous) binary answers to the queries. The queries cannot involve more than two (or a fixed constant number of) elements. Now the labeling of all the elements (or clustering) must be performed based on the noisy query answers. The goal is to recover all the correct labelings while minimizing the number of such queries. The equivalence to locally encodable source codes leads us to find lower bounds on the number of queries required in variety of scenarios. We provide querying schemes based on pairwise 'same cluster' queries - and pairwise AND queries, and show provable performance guarantees for each of the schemes.

关键词： Clustering algorithms Crowdsourcing Labeling source coding Task analysis Decoding Complexity theory Local encoding source coding data compression semi-supervised clustering ‘ same-cluster’ queries

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Fast reinforcement learning algorithms for joint adaptive source coding and transmission control in IoT devices with renewable energy storage

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NEURAL COMPUTING & APPLICATIONS 2022年第5期34卷 3959-3979页

作者： Namjoonia, Farnoosh Sheikhi, Marzieh Hakami, Vesal Iran Univ Sci & Technol Sch Comp Engn Tehran *** Iran Iran Univ Sci & Technol Sch Comp Engn Ctr Excellence Future Networks Tehran Iran

Energy harvesting and source coding are two key techniques that can be exploited to mitigate the device battery limitation in Internet of things (IoT). However, these mitigating techniques come with the expense of adding to the complexity of control and optimization in the digital communication chain. In this paper, to strike a balance between the opposing goals of energy-efficient communication, high-fidelity reconstruction at the IoT gateway, low packet drop ratio, and timeliness of data, we address the delay-constrained joint lossy compression and transmission control problem for an IoT device with rechargeable energy storage. Given the stochastic dynamics emanated from the random nature of the energy harvesting process as well as the fading channel, we formulate a stochastic optimization problem using the formalism of constrained Markov decision process (CMDP) and utilize the standard Lagrangian technique to recast the problem in the unconstrained form. To compute the optimal control policy, we propose a two-timescale stochastic approximation algorithm consisting of some reinforcement learning (RL) algorithms for estimating the CMDP's value function and stochastic gradient descent for estimating the Lagrange multiplier. Specifically, we propose three RL procedures: one based on standard Q-learning, and two accelerated learning procedures, namely post-decision state (PDS) and virtual experience (VE) learning. These algorithms exploit the known system dynamics and batch updates to overcome the slowness caused by the asynchronous updating pattern in Q-learning. Simulation results demonstrate that the proposed PDS and VE learning algorithms speed up the convergence to the optimal control policy by one and two orders of magnitude, respectively.

关键词： source coding Data transmission Internet of things Reinforcement learning

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On the Conditional Smooth Renyi Entropy and its Applications in Guessing and source coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第3期66卷 1674-1690页

作者： Kuzuoka, Shigeaki Wakayama Univ Fac Syst Engn Wakayama 6408510 Japan

A novel definition of the conditional smooth Renyi entropy, which is different from that of Renner and Wolf, is introduced. It is shown that our definition of the conditional smooth Renyi entropy is appropriate for providing lower and upper bounds on the optimal guessing moment in a guessing problem where the guesser is allowed to stop guessing and declare an error. Further a general formula for the optimal guessing exponent is presented. In particular, a single-letterized formula for a mixture of i.i.d. sources is obtained. It is also shown that our definition is appropriate to characterize the optimal exponential moment of the codeword length in the problem of source coding with common side-information available at the encoder and decoder under a constraint on the probability of a decoding error.

关键词： Entropy source coding Decoding Upper bound Error probability Minimization Guessing information-spectrum method side information source coding conditional smooth Renyi entropy

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