Message Loss Research Articles

Cipher chaining key re-synchronization in LPWAN IoT network using a deep learning approach

Low Power Wide Area Network (LPWAN) technology enables low power consumption, long range wireless connectivity, and low cost for strengthening the business cases and achieved eminence as the preferred choice for IoT applications as well. Despite these advantages, they have critical limitations such as very restricted payload size and computation power which creates new challenges in their encryption methods including cipher chaining. A resynchronization mechanism is required in the cipher chaining methods, to sync the keys in case of receiving messages out of order due to events such as packet loss (which is very likely in LPWANs). Since current key resynchronization methods consume a part of the transmitting message, they are not applicable in LPWANs considering their very limited payload size. In this paper, a novel mechanism is proposed for key resynchronization using deep learning. The deep learning is used to learn the pattern of messages and recognize whether or not a message is decrypted corruptly. Then, this model is employed as a tool to identify correct key to decrypt messages. The proposed method enables two parties to keep track of their key sequence without having to add any overload to the payload. Various case studies are provided and simulated to exhibit the efficiency of the proposed method. The case studies proved the robustness of the method in different situations such as single and multiple events loss and different lossy networks. Case studies show up to 99.9% accuracy in key resynchronization with the proposed method after message loss.

Upper and Lower Bounds for the Synchronizer Performance in Systems with Probabilistic Message Loss

In this paper, we revisit the performance of the α-synchronizer in distributed systems with probabilistic message loss as introduced in Függer et al. [Perf. Eval. 93(2015)]. In sharp contrast to the infinite-state Markov chain resp. the exponential-size finite-state upper bound presented in the original paper, we introduce a polynomial-size finite-state Markov chain for a new synchronizer variant alpha ^{prime }, which provides a new upper bound on the performance of the α-synchronizer. Both analytic and simulation results show that our new upper bound is strictly better than the existing one. Moreover, we show that a modified version of the alpha ^{prime }-synchronizer provides a lower bound on the performance of the α-synchronizer. By means of elaborate simulation results, we show that our new lower bound is also strictly better than the lower bound presented in the original paper.

Uniform reliable broadcast in anonymous distributed systems with fair lossy channels

Uniform reliable broadcast (URB) is an important abstraction in distributed systems, offering delivery guarantee when spreading messages between processes. Informally, URB guarantees that if a process (correct or not) delivers a message m, then all correct processes deliver m. This abstraction has been extensively investigated in distributed systems where all processes have unique identifiers. Furthermore, the majority of papers in the literature usually assume that the communication channels of the system are reliable, which is not always the case in real systems. In this paper, the URB abstraction is investigated in anonymous asynchronous message passing distributed systems with process crash failures and fair lossy channels. For that, we assume the availability of a random number generator that generates unique global values with very high probability. Firstly, a simple URB algorithm is given assuming a majority of correct processes. Then, we prove the impossibility of solving URB without a majority of correct processes if no failure detector is used. Subsequently, a new failure detector class $$A{\varTheta }$$ is proposed, which can be used to implement URB with any number of correct processes. However, the two previous URB algorithms are non-quiescent because every correct process, to offset the loss of messages caused by fair lossy channels, has to broadcast all URB $$\_$$ delivered messages forever. Hence, a perfect anonymous failure detector $$AP^*$$ is proposed, together with $$A{\varTheta }$$ , to make the URB algorithm quiescent. Finally, we discuss an alternative failure detector $$A{\varTheta }P^*$$ , which combines the properties of $$A{\varTheta }$$ and $$AP^*$$ .

Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing

Cloud computing has seen rapid growth in the last decade, as a result of this there is an increasing concern about the energy requirement of cloud data centres. One approach to tackle this issue is dynamic virtual machine consolidation (DVMC) where virtual machines (VMs) are packed into fewer hosts, while hosts which have no VMs are placed into a hibernate mode. DVMC is traditionally solved with strategies that build on centralised topologies. One disadvantage of these solutions is that they don′t scale well in very large data centres as the manager node becomes a bottleneck and a single point of failure. The nature of the problem lends itself to a decentralised solution which is preferred over a centralised one when a problem is: inherently modular, large in scale, in a very dynamic environment, and when communication channels can experience message delays and loss. We propose Gossip Contracts (GC), a new multi-agent framework for crafting decentralised co-operation strategies. GC is inspired by the Gossip and Contract Net protocols. Using GC we developed a GC-based DVMC strategy and compared it to two popular strategies: Sercon, a centralised strategy, and ecoCloud, a distributed strategy. One of the comparison experiments uses Google cluster-usage traces; a dataset of real usage data from a Google data centre. The GC-based strategy performs best with respect to SLA Violations, and is similar to or outperforms other strategies with respect to power consumption. By its decentralised nature, GC does not have a single point of failure.

Indecision and delays are the parents of failure\u2014taming them algorithmically by synthesizing delay-resilient control

The possible interactions between a controller and its environment can naturally be modelled as the arena of a two-player game, and adding an appropriate winning condition permits to specify desirable behavior. The classical model here is the positional game, where both players can (fully or partially) observe the current position in the game graph, which in turn is indicative of their mutual current states. In practice, neither sensing and actuating the environment through physical devices nor data forwarding to and from the controller and signal processing in the controller are instantaneous. The resultant delays force the controller to draw decisions before being aware of the recent history of a play and to submit these decisions well before they can take effect asynchronously. It is known that existence of a winning strategy for the controller in games with such delays is decidable over finite game graphs and with respect to omega -regular objectives. The underlying reduction, however, is impractical for non-trivial delays as it incurs a blow-up of the game graph which is exponential in the magnitude of the delay. For safety objectives, we propose a more practical incremental algorithm successively synthesizing a series of controllers handling increasing delays and reducing the game-graph size in between. It is demonstrated using benchmark examples that even a simplistic explicit-state implementation of this algorithm outperforms state-of-the-art symbolic synthesis algorithms as soon as non-trivial delays have to be handled. We furthermore address the practically relevant cases of non-order-preserving delays and bounded message loss, as arising in actual networked control, thereby considerably extending the scope of regular game theory under delay.

Review of random multiple access methods for massive machine type communication

Introduction: Intensive research is currently underway in the field of data transmission systems for the Internet of Things in relation to various scenarios of Massive Machine Type Communication. The presence of a large number of devices in such systems necessitates the use the methods of random multiple access to a common communication channel. It is proposed in some works to increase the channel utilization efficiency by the use of error correction coding methods for conflict resolution (Coded Random Access). The vast variety of options for using such communication systems has made it impossible to compare algorithms implementing this approach under the same conditions. This is a problem that restrains the development of both the theory and practice of using error correction code methods for conflict resolution. Purpose: Developing a unified approach to the description of random multiple access algorithms; performing, on the base on this approach, a review and comparative analysis of algorithms in which error correction code methods are used for conflict resolution. Results: A model of a random multiple access system is formulated in the form of a set of assumptions that reflect both the features of various scenarios of Massive Machine Type Communication and the main features of random multiple access algorithms, including Coded Random Access approaches. The system models are classified by the following features: 1) a finite or infinite number of subscribers; 2) stable, unstable or metastable systems; 3) systems with retransmissions or without them; 4) systems with losses or without them. For a lossy system, the main characteristics are Throughput (the proportion of successfully delivered messages) and Packet Loss Rate (probability of a message loss). For a lossless system, the basic characteristics are the algorithm speed and the average delay. A systematic review and comparative analysis of Coded Random Access algorithms have been carried out. The result of the comparative analysis is presented in a visual tabular form. Practical relevance: The proposed model of a random multiple access system can be used as a methodological basis for research and development of random multiple access algorithms for both existing and new scenarios of Massive Machine Type Communication. The systematic results of the review allow us to identify the promising areas of research in the field of data transmission systems for the Internet of Things.

Performance Analysis of Onshore NB-IoT for Container Tracking During Near-the-Shore Vessel Navigation

This article aims to put forward the utilization of onshore narrowband IoT (NB-IoT) infrastructure for tracking of containers transported by marine cargo vessels while operating near the coastline. We introduce and evaluate three connectivity strategies, including direct sensor-to-onshore base station (BS) transmission as well as two relay-aided schemes using dedicated vessel-BS or unmanned-aerial-vehicle (UAV)-mounted BS as intermediate nodes. To assess and compare the proposed schemes in terms of the message loss and delay metrics as well as sensor lifetimes, we first employ stochastic geometry to characterize the connectivity process with the onshore deployment and then resort to system-level simulations. Our results indicate that the direct access option suffers from the poorest performance. The relay-based alternatives allow to dramatically improve the system operation by effectively distributing the transmission requests over time at the relay side and thus mitigating contention. Furthermore, gains enabled with UAV relaying are due to extended coverage that increases the available BS density. The considered relaying operation may help tolerate intermittent connectivity across a broad range of system parameters.

Stability and Convergence of a Message-Loss-Tolerant Rendezvous Algorithm for Wireless Networked Robot Systems

This article considers the problem of swarm rendezvous when robots exchange local coordination messages through an unreliable wireless communication network (i.e., message-loss occurs). First, a discrete-time second-order consensus algorithm is provided to deal with the effects of unreliable channels on wireless networked robot (WNR) systems, and drive the robots to a given geometric formation. Then, necessary and sufficient conditions for the controlled WNR to converge to a desired formation, even in the presence of messages loss, are formulated and simulatively validated. The proposed conditions provide to the WNR designer a minimal topology connectivity requirement, and a relation among algorithm step-size and control gains to be fulfilled for guaranteeing swarm rendezvous.

Reinforced Secure Gossiping Against DoS Attacks in Post-Disaster Scenarios

During and after a disaster, the perceived quality of communication networks often becomes remarkably degraded with an increased ratio of packet losses due to physical damages of the networking equipment, disturbance to the radio frequency signals, continuous reconfiguration of the routing tables, or sudden spikes of the network traffic, e.g., caused by the increased user activity in a post-disaster period. Several techniques have been introduced so far (mainly using data retransmission mechanisms) to tolerate such circumstances. Among them, gossiping has been shown to be efficient in the recovery from message losses. However, a conventional gossiping scheme may exhibit security problems, which can be exploited for further attacks (such as Denial of Service - DoS attack). For instance, the flooding method used by the gossiping can be used to forward the traffic towards many vulnerable nodes to drain their resources and compromise them. Typically, protection against DoS attacks is realized by using cryptographic primitives. However, their scalability limits and costs make them improper for emergency communications after a disaster. In this article, we introduce an approach based on reinforcement learning and game theory to protect the gossiping scheme from DoS attacks without incurring the costs of cryptographic primitives. In our method, nodes properly select which requests to satisfy, which in turn helps other nodes to avoid receiving manipulated gossip messages from malicious and colluded nodes. Additionally, our method operates without exploiting any cryptographic primitives, which prevents excessive energy waste that is undesired in post-disaster resilient networking. Simulation experiments performed in OMNeT++ confirmed the advantages of our approach over the reference schemes in terms of reliability, security, overhead, latency, and power efficiency.

Dynamic Self-Organizing Leader-Follower Control in a Swarm Mobile Robots System Under Limited Communication

The leader-follower model is found efficient for robot swarm exploration tasks. When a swarm of mobile robots collaboratively explore an unknown environment with limited communication, such as communication delay or even message loss, it is necessary to adaptively re-group robots according to the dynamic communication conditions and task goals. In this paper, we propose to analyze the leader-follower topology in a graph fashion and employ Ratio Cut of the proposed graph for membership re-assignment. We take each robot as a node and consider both the communication delay and the goal, i.e., exploring towards unknown area, as the edge weight. Then we use the Laplacian matrix to bipartition the graph repeatedly to optimize group partition. Simulation results validate the effectiveness of the proposed method.

PDMAC: A Priority-Based Enhanced TDMA Protocol for Warning Message Dissemination in VANETs.

Vehicular ad hoc networks (VANETs) are the key enabling technology for intelligent transportation systems. Carrier-sense multiple access with collision avoidance (CSMA/CA) is the de facto media access standard for inter-vehicular communications, but its performance degrades in high-density networks. Time-division multiple access (TDMA)-based protocols fill this gap to a certain extent, but encounter inefficient clock synchronization and lack of prioritized message delivery. Therefore, we propose a priority-based direction-aware media access control (PDMAC) as a novel protocol for intra-cluster and inter-cluster clock synchronization. Furthermore, PDMAC pioneers a three-tier priority assignment technique to enhance warning messages delivery by taking into account the direction component, message type, and severity level on each tier. Analytical and simulation results validate the improved performance of PDMAC in terms of clock synchronization, channel utilization, message loss rate, end-to-end delays, and network throughput, as compared with eminent VANET MAC protocols.

Reconfiguration and Message Losses in Parameterized Broadcast Networks

Broadcast networks allow one to model networks of identical nodes communicating through message broadcasts. Their parameterized verification aims at proving a property holds for any number of nodes, under any communication topology, and on all possible executions. We focus on the coverability problem which dually asks whether there exists an execution that visits a configuration exhibiting some given state of the broadcast protocol. Coverability is known to be undecidable for static networks, i.e. when the number of nodes and communication topology is fixed along executions. In contrast, it is decidable in PTIME when the communication topology may change arbitrarily along executions, that is for reconfigurable networks. Surprisingly, no lower nor upper bounds on the minimal number of nodes, or the minimal length of covering execution in reconfigurable networks, appear in the literature. In this paper we show tight bounds for cutoff and length, which happen to be linear and quadratic, respectively, in the number of states of the protocol. We also introduce an intermediary model with static communication topology and non-deterministic message losses upon sending. We show that the same tight bounds apply to lossy networks, although, reconfigurable executions may be linearly more succinct than lossy executions. Finally, we show NP-completeness for the natural optimisation problem associated with the cutoff.

Fast Feedback Control over Multi-hop Wireless Networks with Mode Changes and Stability Guarantees

Closing feedback loops fast and over long distances is key to emerging cyber-physical applications; for example, robot motion control and swarm coordination require update intervals of tens of milliseconds. Low-power wireless communication technology is preferred for its low cost, small form factor, and flexibility, especially if the devices support multi-hop communication. Thus far, however, feedback control over multi-hop low-power wireless networks has only been demonstrated for update intervals on the order of seconds. To fill this gap, this article presents a wireless embedded system that supports dynamic mode changes and tames imperfections impairing control performance (e.g., jitter and message loss), and a control design that exploits the essential properties of this system to provably guarantee closed-loop stability for physical processes with linear time-invariant dynamics in the presence of mode changes. Using experiments on a cyber-physical testbed with 20 wireless devices and multiple cart-pole systems, we are the first to demonstrate and evaluate feedback control and coordination with mode changes over multi-hop networks for update intervals of 20 to 50 milliseconds.

Model checking of in-vehicle networking systems with CAN and FlexRay

An in-vehicle networking (IVN) system consists of electronic components that are connected by buses and communicate through multiple protocols according to their requirements. In practice, intelligent vehicles need to exchange data between subsystems that use various protocols, such as the controller area network (CAN) and FlexRay. Such systems are more likely to encounter delays and message loss during transmission, presenting serious safety issues. Moreover, IVN systems are extremely complicated because of their large number of nodes, multiple communication protocols, and diverse topologies. As a result, it is difficult to check the timed properties of the system directly and accurately. In this paper, we present an appropriate abstraction for modeling IVN systems that utilize CAN and FlexRay during the design phase. The timed properties of communication are analyzed using the UPPAAL platform. As there are numerous IVN system structures, a framework is developed to build a model for an IVN system design. The model is to verify the transmission of messages between different protocols. We evaluate the validity, applicability, and reusability of the framework and show the performance of the framework for verifying IVN system models.

Steganografi Pada Digital Image Menggunakan Metode Least Significant Bit Insertion

<span lang="SV">Steganography is a way to hide messages or confidential data in a medium called a carrier file. Embedding is done by the Least Significant Bit Insertion method, which is to replace the lowest bit of Red Green Blue (RGB) each pixel with the data bit you want to insert. With this method the difference between pixels that have not been pasted by messages and pixels that have been pasted by messages cannot be distinguished by human eye sight. Because the LSB insertion method is used, it is necessary to consider the type of digital image format used, this is necessary to avoid the loss of messages when extracting. And the best digital image format used is the 24-bit BMP because the BMP format is lossless compression</span>

Integrated Robotic and Network Simulation Method.

The increasing use of mobile cooperative robots in a variety of applications also implies an increasing research effort on cooperative strategies solutions, typically involving communications and control. For such research, simulation is a powerful tool to quickly test algorithms, allowing to do more exhaustive tests before implementation in a real application. However, the transition from an initial simulation environment to a real application may imply substantial rework if early implementation results do not match the ones obtained by simulation, meaning the simulation was not accurate enough. One way to improve accuracy is to incorporate network and control strategies in the same simulation and to use a systematic procedure to assess how different techniques perform. In this paper, we propose a set of procedures called Integrated Robotic and Network Simulation Method (IRoNS Method), which guide developers in building a simulation study for cooperative robots and communication networks applications. We exemplify the use of the improved methodology in a case-study of cooperative control comparison with and without message losses. This case is simulated with the OMNET++/INET framework, using a group of robots in a rendezvous task with topology control. The methodology led to more realistic simulations while improving the results presentation and analysis.

Behavior-Based Control for an Aerial Robotic Swarm in Surveillance Missions.

Aerial robotic swarms have shown benefits for performing search and surveillance missions in open spaces in the past. Among other properties, these systems are robust, scalable and adaptable to different scenarios. In this work, we propose a behavior-based algorithm to carry out a surveillance task in a rectangular area with a flexible number of quadcopters, flying at different speeds. Once the efficiency of the algorithm is quantitatively analyzed, the robustness of the system is demonstrated with 3 different tests: loss of broadcast messages, positioning errors, and failure of half of the agents during the mission. Experiments are carried out in an indoor arena with micro quadcopters to support simulation results. Finally, a case study is proposed to show a realistic implementation in the test bed.

Fault-tolerant least squares solvers for wireless sensor networks based on gossiping

Many applications in large loosely connected distributed networks (such as wireless sensor networks) require the distributed solution of linear least squares (dLLS) problems. Ideally, a truly distributed algorithm should require very little coordination between the nodes. This favours algorithms which do not require a fusion centre, cluster heads or any multi-hop communication.We present the novel dLLS solver GLS-IR for overdetermined linear systems. We investigate two variants of our novel solver, one of them based on the semi-normal equations, the other based on the normal equations. Both are combined with iterative refinement in mixed precision, which not only stabilises the methods but also decreases the communication cost. In GLS-IR, all communication between nodes is contained within a gossip-based algorithm for distributed aggregation, which limits the communication of each node to its immediate neighbourhood. Therefore, GLS-IR benefits directly from efficient and fault-tolerant algorithms for distributed aggregation. We use a fault-tolerant alternative to the push-sum method, the push-flow algorithm, which is able to recover from silent message loss and temporary or permanent link failures.We analytically compare the communication cost of GLS-IR to existing truly distributed algorithms. Since the theoretical analysis contains problem-dependent parameters, numerical experiments are needed in order to get a complete picture. Our simulation experiments illustrate a significantly reduced communication cost of GLS-IR compared to other existing truly distributed least squares solvers. We also illustrate that due to the properties of iterative refinement and push-flow, GLS-IR can achieve a result accurate to machine precision even if a high amount of message loss occurs.

Distributed Cooperative Economic Optimization Strategy of a Regional Energy Network Based on Energy Cell–Tissue Architecture

The conventional centralized control method can effectively solve the influence of system power imbalance on the optimal dispatching of a power network and stabilize the power fluctuation of tie lines when the control precision is relatively high. However, when there are disturbances and uncertainties in the system, the robustness is insufficient. The distributed control method in economic optimization scheduling has the advantages of simple communication and high reliability and is well adapted to the energy dispersion characteristics of a distributed generator within the regional energy network. However, the control accuracy is slightly less than that of the centralized control method, and when the distributed power encounters a random input or exit, the corresponding sparse network matrix needs to be updated every time, complicating the use of this system for economic operation. In addition, when message loss or communication noise occurs in the communication path, the robustness of distributed control is greatly reduced. To address these issues, this paper proposes a novel power allocation framework to solve the economic optimization problem of a regional energy network that requires only local information exchange among neighboring energy cells and tissues. Correspondingly, to meet the supply–demand balance, a distributed cooperative approach based on the equal incremental principle is used to impart decentralized autonomy to the whole system. In addition, the concept of virtual consistency variables is introduced to manage topological change caused by power excursions in the energy cell and to implement plug-and-play capabilities. Relative to the conventional collaborative control method, the case studies demonstrate the scalability, plug-and-play capability, and robustness of decentralized autonomous control strategies in terms of communication delay, communication failure, and message loss, among other aspects.

A Novel Chaining Encryption Algorithm for LPWAN IoT Network

LPWAN IoT networks (such as Sigfox, LoRaWAN, and NB-IoT) become more applicable every day in the industry. Despite their unique advantages, these technologies have many limitations, including low computing power and transmission rate, and very limited payload size. These limitations cause many challenges in the cryptography such as chaining ciphers mode of encryption. In this mode, a packet loss in the transmission leads to disruption in the ciphers chain and consequently, receiving corrupted messages by the receiver. None of the current encryption approaches can be used in LPWAN due to the serious restrictions on the payload size and the limited downlink connectivity. In this paper, we propose a novel chaining encryption method that can be used in any narrowband and lossy network including LPWAN. The proposed method introduces a module named appropriate key finder (AKF) which assigns a dedicated key to each message using hash functions. The AKF mechanism is based on finding a key which its hash is equal to a part of the message. It can handle message loss and keep parties synchronized without using any part of the payload; however, it fails if a collision is found in the hash function. The proposed method is the first one of its kind that is based on a stochastic approach, instead of the deterministic ones. The paper also reviews the statistical properties of the proposed method and the failure probability. Moreover, the simulation and experiment results of some case studies are presented to show the efficiency of the method in practice.