This report describes the progress made towards the completion of a specific task on error-correcting coding. The proposed research consisted of investigating the use of modulation block codes as the inner code of a concatenated coding system in order to improve the overall space link communications performance. The study proposed to identify and analyze candidate codes that will complement the performance of the overall coding system which uses the interleaved RS (255,223) code as the outer code.

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Error-correction coding

Internet of Things (IoT) entities compile a massive volume of sensing data and transmit it to the cloud for processing and reasoning. Reliable and secure data aggregation and forwarding in IoT incorporates resource-constrained low-power and lossy devices that served diverse and sensitive applications with special obligations is a significant challenge for IoT. This paper proposes Reliable Data Dissemination for the Internet of Things Using Harris Hawks Optimization (RDDI) scheme, which is a secure data diffusion mechanism that accoutered a fuzzy hierarchical network model for Wireless Sensor Networks (WSN) based IoT. RDDI discloses attacks and monitors the behavior of nodes information exchange processes. Our scheme prowls to synthesize routing capabilities, energy-aware and geographic data circulation, and fuzzy clustering to provide a reliable, nature-inspired optimized routing called Harris Hawks Optimization (HHO) algorithm for IoT. The performance of RDDI, under five metrics of reliability, end-to-end delay, energy consumption, computational overhead as well as packet forwarding distance in multi-cluster scenarios, is evaluated with three comparative approaches. Findings of simulations reveal that RDDI achieves a reliable strategy and preferable achievement over the other three disposals.

Reliable data dissemination for the Internet of Things using Harris hawks optimization

Graph Theory with Applications to Engineering and Computer ... This outstanding introductory treatment of graph theory and its applications has had a long life in the instruction of advanced undergraduates and graduate students in all areas that require knowledge of this subject. The first nine chapters constitute an excellent overall introduction, requiring only some knowledge of set theory and matrix algebra.

Graph theory with applications to engineering and computer science, by Narsingh Deo. Pp xvii, 478. 1974. SBN 0 13 363473 6 (Prentice-Hall)

Practically all known good constructive coding techniques for bandlimited channels, including lattice codes and various trellis-coded modulation schemes, can be characterized as coset codes. A coset code is defined by a lattice partition Lambda / Lambda ' and by a binary encoder C that selects a sequence of cosets of the lattice Lambda '. The fundamental coding gain of a coset code, as well as other important parameters such as the error coefficient, the decoding complexity, and the constellation expansion factor, are purely geometric parameters determined by C Lambda / Lambda '. The known types of coset codes, as well as a number of new classes that systematize and generalize known codes, are classified and compared in terms of these parameters. >

Coset codes. I: Introduction and geometrical classification

Introduction to formal languages and automata

With billions of devices adding up to the internet, broadly termed as Internet of Things (IoT), the need for reliable communication, distributed storage and computation has seamlessly increased. At this juncture, need for reliable communication, distributed storage and computation, adoption of error correcting codes and erasure codes plays a significant role. In this chapter, we give an overview of construction of erasure codes required for reliable communication with emphasis on Internet of Things (IoT) communication which have wireless sensors or sensor networks as its core. Wireless sensors form an integral part of Internet of Things (IoT) devices bridging the virtual world and the real world. Achieving reliability in such networks is highly desirable due to their broad range of applications. The discussed erasure codes in this chapter can be directly employed or with little modification in the context of reliable communication in Internet of Things. In this chapter, the two methods of information transmission, end-to-end transmission and hop-by-hop transmission, prevalent in digital communication scenario is discussed in detail with emphasis on with and without erasure coding. Also, the erasure codes used extensively in the context of achieving reliability in wireless sensor communication namely Reed-Solomon codes, Fountain codes and Decentralized Erasure codes are discussed and compared. This chapter serves as a starting point for researchers interested in working on reliability aspects of communication in Internet of Things embedded with wireless sensors and cyber physical systems.

Erasure Codes for Reliable Communication in Internet of Things (IoT) Embedded with Wireless Sensors

Networks consisting of wireless sensors are extensively used in many applications. Decentralized Erasure Codes (DEC) were introduced to store the sensed data in the wireless sensor network itself before transmitting the sensed data from wireless nodes to gateway or query nodes. Data at the failed nodes can be reconstructed by accessing other nodes in the network in DEC setup. In a traditional DEC setup, it is required to access k nodes out of n nodes to reconstruct the data at the failed node. Also, the reconstruction at failed node is subjected to intruder attacks raising security concerns. To reduce the number of nodes required to reconstruct the data at failed nodes and to ensure communication security, in this paper, decentralized erasure codes were constructed from optimal locally recoverable codes and Blom’s key pre-distribution protocol, which exploits the generator matrix nature of constructed code, was implemented. From the simulations, we can infer that the proposed scheme performs better than other existing methods that use Reed–Solomon codes in terms of network load and error count per sent packet. Furthermore, it is shown that the proposed scheme ensures secure and efficient communication between nodes to overcome intruder interference.

Reliable and secure data communication in wireless sensor networks using optimal locally recoverable codes

Wireless Sensor Networks form the integral part of Cyber Physical Systems. Large number of sensors which have been deployed in the field help in sensing and controlling applications. With the growing popularity of wireless sensor networks, a variety of techniques have been proposed or employed for increasing the performance and efficiency of such systems. One such technique is usage of Decentralized Erasure Codes to reliably communicate and obtain information over the network. In this work, we are constructing decentralized erasure code setup from the optimal locally recoverable codes and analyze the performance, significance of such a construction. Proposed model is evaluated through simulation in terms of network load and error count per sent packet. From the results, it can be inferred that the proposed model reduces the network load in reconstructing the message or information at the lost node and there by increases the system efficiency.

Efficient data reconstruction in sensor networks using optimal locally recoverable codes

Low Density Parity Check (LDPC) codes have been of great interest to researchers due to its low complexity in encoding as well as decoding. Since the introduction of Turbo codes in 1993, importance of LDPC codes has been widely explored. Various techniques have been introduced for encoding and decoding of low density parity check codes based on algebraic structures, codes on graphs, etc. In this paper, a new method of constructing binary and nonbinary LDPC-like codes from Kernel codes defined over groups is discussed. Also, we show that constructions of binary and nonbinary LDPC-like codes are particular cases of our proposed method.

Construction of Binary and Nonbinary LDPC-like Codes from Kernel Codes

Concatenated codes introduced by Forney in 1966 received wide attention due to their extensive usage in space missions. Thereafter, many concatenated codes were constructed on the similar lines and...

C. Pavan Kumar

Papers

Erasure Codes for Reliable Communication in Internet of Things (IoT) Embedded with Wireless Sensors

Reliable and secure data communication in wireless sensor networks using optimal locally recoverable codes

Efficient data reconstruction in sensor networks using optimal locally recoverable codes

Construction of Binary and Nonbinary LDPC-like Codes from Kernel Codes

Concatenated kernel codes