Management of Caching Policies and Redundancy Over Unreliable Channels

Problem statement: Causal ordering is used in Mobile Distributed Systems (MDS) to reduce the non-determinism induced by four main aspects: host mobility, asynchronous execution, unpredictable communication delays and unreliable communication channels. Some causal protocols have been proposed for MDS. All of these protocols in order to ensure the causal order in unreliable channels use the method of Automatic Repeat Request (ARQ). They detect a lost message and carry out the retransmission of this message. This approach was not recommended in a real time mobile distributed system because it increased the transmission delay of the data and the overhead sent in the communication channels. Approach: In this study, we proposed a protocol that ensured the causal order of messages in unreliable and asynchronous MDS. In our protocol, the detection and recovery of lost messages was achieved by the method of Forward Error Correction (FEC) in a distributed form. One interesting aspect of our Causal-FEC protocol was that the redundant information sent in the wired and wireless communication channels is dynamically adapted to the behavior of the system. Results: Our protocol was efficient in terms of the overhead attached per message, the computational cost and the storage control information at a mobile host. Conclusion: The present study is one of the first works on causal algorithms based on forward error recovery in mobile networks.

Robust and flexible speech codecs are more and more required by speech communication over unreliable channels such as Internet. In this paper, a novel multiple description (MD) sinusoidal speech codec is proposed. This codec is based on sinusoidal and equivalent rectangular bands (ERB) noise model. It can provide relatively high transmission reliability as well as good coding efficiency. And the lost packet doesn't affect the state recovery of this state-less MD codec. Therefore it is very suitable to unreliable and band limited channel such as Internet

In recent years, RFID technologies have been widely used in real-life applications, including supply chain manage-ment, warehouse tracking, etc. One of the concerns is the estimation of the number of interested tags. The existence of unknown tags will affect normal operation and management for RFID systems. Existing protocols for estimating the number of unknown tags generally assume ideal communication channels. In practice, there may exist environment interference that affects the transmission from tags to a RFID reader. In this paper, we study the problem of estimating the number of unknown tags under unreliable channels, and propose a cardinality estimation scheme CEUT(Cardinality Estimation for Unknown Tags under unreliable channels). The reader collects responses from all tags after running the Aloha protocol. The number of non-empty slots in the response frame increases due to the presence of unknown tags is designed based on the number of empty slots in the predicted frame converted into non-empty slots in the response frame and the channel noise parameter. The simulation results show that, under the unreliable channel, the estimation result scheme yielded by CEUT is more robust than other existing schemes, and can achieve therequired estimation accuracy.

Least-recently-used (LRU) caching and its variants have conventionally been used as a fundamental and critical method to ensure fast and efficient data access in computer and communication systems. Emerging data-intensive applications over unreliable channels, e.g., mobile edge computing and wireless content delivery networks, have imposed new challenges in optimizing LRU caching systems in environments prone to failures. Most existing studies focus on reliable channels, e.g., on wired Web servers and within data centers, which have already yielded good insights with successful algorithms on how to reduce cache miss ratios. Surprisingly, we show that these widely held insights do not necessarily hold true for unreliable channels. We consider a single-hop multi-cache distributed system with data items being dispatched by random hashing. The objective is to achieve efficient cache organization and data placement. The former allocates the total memory space to each of the involved caches. The latter decides data routing strategies and data replication schemes. Analytically we characterize the unreliable LRU caches by explicitly deriving their asymptotic miss probabilities. Based on these results, we optimize the system design. Remarkably, these results sometimes are counterintuitive, differing from the ones obtained for reliable caches. We discover an interesting phenomenon: asymmetric cache organization is optimal even for symmetric channels. Specifically, even when channel unreliability probabilities are equal, allocating the cache spaces unequally can achieve a better performance. We also propose an explicit unequal allocation policy that outperforms the equal allocation. In addition, we prove that splitting the total cache space into separate LRU caches can achieve a lower asymptotic miss probability than resource pooling that organizes the total space in a single LRU cache. These results provide new and even counterintuitive insights that motivate novel designs for caching systems over unreliable channels. They can potentially be exploited to further improve the system performance in real practice.

The Internet has caused the skills of world wide-scale collective problem solving, which is known as crowdsourcing that connects the individuals around the world to cooperate and solve the multifarious complex problem. However, due to the openness prominent features of crowdsourcing, it conceives some antisocial behaviors, such as sabotaging, attacking, plagiarizing, and manipulating the solution obtained by collective individuals. Crowdsourcing contest dilemma game was recently proposed, which shows that the malicious behavior is the norm in crowdsourcing competitions. In this paper, we extend the two-stage game by introducing the unreliable channels to analyze the process of equilibrium based on game theory. Under the current framework structure, we first analyze the situation in the second stage (to attack or not), and then take a step back and discuss the players' decisions (crowdsource or in-house) in the first stage. We find that the unreliable channels would affect a less desirable total profit to some extent, what's more, there are still crowdsourcing contest dilemmas in the crowdsourcing competitions under the unreliable channels.

Least-recently-used (LRU) caching and its variants have conventionally been used as a fundamental and critical method to ensure fast and efficient data access in computer and communication systems. Emerging data-intensive applications over unreliable channels, e.g., mobile edge computing and wireless content delivery networks, have imposed new challenges in optimizing LRU caching in environments prone to failures. Most existing studies focus on reliable channels, e.g., on wired Web servers and within data centers, which have already yielded good insights and successful algorithms. Surprisingly, we show that these insights do not necessarily hold true for unreliable channels. We consider a single-hop multi-cache distributed system with data items being dispatched by random hashing. The objective is to design efficient cache organization and data placement that minimize the miss probability. The former allocates the total memory space to each of the involved caches. The latter decides data routing and replication strategies. Analytically, we characterize the asymptotic miss probabilities for unreliable LRU caches, and optimize the system design. Remarkably, these results sometimes are counterintuitive, differing from the ones obtained for reliable caches. We discover an interesting phenomenon: allocating the cache space unequally can achieve a better performance, even when channel reliability levels are equal. In addition, we prove that splitting the total cache space into separate LRU caches can achieve a lower asymptotic miss probability than organizing the total space in a single LRU cache. These results provide new and even counterintuitive insights that motivate novel designs for caching systems over unreliable channels.

In this paper, we focus on the remote real-time close-loop control scenarios, where the state of observation process is collected by the sensor and timely transmitted to the remote control center (RCC) over an unreliable channel or network, followed by a control command generated from RCC fed back to the actuator, which is called remote control. The age of information (AoI) is widely used to capture the timeliness. We pay attention to the age outage, which is defined as the probability that the peak age exceeds a certain threshold. Due to the existence of long link delay and channel unreliability, the observation process is likely to be uncontrolled, which may degrade the AoI. We first adopt always remote control (always-RC) and analyze the impact of long delay and channel unreliability on age outage. An interesting result is that long delay and channel unreliability has the potential to decrease the age outage probability. To improve age outage, we further propose a local-assisted joint control policy by introducing the smart sensor that is capable of processing and controlling. Age outage probability under local-assisted joint control is then analyzed. Results show that local-assisted joint control policy has the effectiveness in improving the performance of age outage by setting suitable local control times.

An inherent assumption for packet forwarding in ad hoc networks is that the nodes will cooperate i.e., nodes can rely in each other. Thus, it is extremely important that cooperation is induced and achieved in the network. In this paper, we use game theory to analyze the necessary and sufficient conditions to enforce cooperation enforced, especially when a node cannot perfectly monitor other nodespsila behaviors. We analyze a credit exchange method under a general unreliable channel and show that the packet forwarding probability can be adjusted through proper design of incentives, which in turn can be used to attain the desired Nash Equilibrium. We extend our discussion to repeated games and take several well-known strategy profiles and derive the conditions under which the cooperation can lead to a subgame perfect Nash equilibrium. In particular, we show how the unreliable channel can affect the conditions and how a reputation based strategy leads to subgame perfection even under imperfect monitoring. We further investigate collusion resistance and cooperation coalition formation using evolutionary game theory. Mathematical proofs show the existence of an upper bound on the population share of the non-cooperative nodes for an evolutionarily non-stable strategy that enforces full cooperation. This bound is shown to depend on the nodespsila belief on the continuity of the game.

Smart card-based agents for fair non-repudiation

A.V. Aho et al. (Comput. Math. Applic., vol.8, p.205-14, 1982) used communicating finite-state machines to model synchronous protocols for reliable communication across unreliable channels. Their ideas are extended to modeling asynchronous protocols for communication across unreliable channels using finite-state machines communicating via an unreliable shared memory. Lower bounds on the size of machines and the number of symbols in the transmission alphabet required to achieve reliable communication are established. Two types of finite-state machines and two fault models for the shared memory are considered. In each case it is shown that there are robust protocols for deletion and insertion errors. It is also shown that there are no robust protocols for mutation errors. In contrast, in the synchronous case, robust protocols exist for all of these types of errors.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Over the last decade, the Age of Information has emerged as a key concept and metric for applications where the freshness of sensor-provided data is critical. Limited transmission capacity has motivated research on the design of tractable policies for scheduling information updates to minimize Age of Information cost based on Markov decision models, in particular on the restless multi-armed bandit problem (RMABP). This allows the use of Whittle’s popular index policy, which is often nearly optimal, provided indexability (index existence) is proven, which has been recently accomplished in some models. We aim to extend the application scope of Whittle’s index policy in a broader AoI scheduling model. We address a model with no buffers incorporating random packet arrivals, unreliable channels, and nondecreasing AoI costs. We use sufficient indexability conditions based on partial conservation laws previously introduced by the author to establish the model’s indexability and evaluate its Whittle index in closed form under discounted and average cost criteria. We further use the index formulae to draw insights on how scheduling priority depends on model parameters.

This paper studies LTI one-degree-of-freedom networked control architectures built around LTI SISO plants. The feedback path comprises an unreliable channel that drops data in an i.i.d. fashion. We extend known results to show that there exists a second order moments equivalence between the situation examined and an auxiliary feedback loop where the unreliable channel has been replaced by an additive i.i.d. noise channel that has an equality signal-to-noise ratio constraint. We then use these insights to design optimal controllers. We also establish a necessary and sufficient condition on the successful transmission probability that allows for the design of a controller that guarantees MSS in the considered setup. Our proposal does not require packet arrival acknowledgements. Thus, our results give necessary and sufficient conditions for MSS in an output-feedback control architecture with UDP-like protocols.

security of bio-metric information - finger print, retina mapping, DNA mapping and some other chemical and biological modified genes related information - transfer through low bandwidth and unreliable or covert channel is challenging task. Therefore, Security of biometric information is essential requirement in this fast developing communication world. Thus, in this paper, we propose efficient and effective mechanism for confidentiality and authentication for biometric information transmitted by using arithmetic encoding representation over low bandwidth and unreliable channel. It enhances the speed of encryption, decryption and authentication process. It uses arithmetic encoding scheme and public key cryptography e.g. modified version of RSA algorithm called RSA-2 algorithm.

We consider the verification of a particular class of infinite-state systems, namely systems consisting of finite-state processes that communicate via unbounded lossy FIFO channels. This class is able to model e.g. link protocols such as the Alternating Bit Protocol and HDLC. In an earlier paper, we showed that several interesting verification problems are decidable for this class of systems, namely (1) the reachability problem: is a set of states reachable from some other state of the system, (2) safety property over traces formulated as regular sets of allowed finite traces, and (3) eventuality properties: do all computations of a system eventually reach a given set of states. In this paper, we show that the following problems are undecidable, namely The model checking problem in propositional temporal logics such as Propositional Linear Time Logic (PTL) and Computation Tree Logic (CTL). The problem of deciding eventuality properties with fair channels: do all computations eventually reach a given set of states if the unreliable channels are fair in the sense that they deliver infinitely many messages if infinitely many messages are transmitted. This problem can model the question of whether a link protocol, such as HDLC, will eventually reliably transfer messages across a medium that is not permanently broken. The results are obtained through a reduction from a variant of Post's Correspondence Problem.KeywordsModel CheckSafety PropertyLabel Transition SystemComputation Tree LogicEventuality PropertyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

To alleviate the ever-increasing data demands, edge caching plays a crucial role in improving the performance of system, especially in data-intensive applications. Previous works mainly focus the caching policy over reliable channels. For unreliable channel scenarios, the system performance is jointly affected by the user preference and the channel reliability, whereas both the user preference and the reliability are unknown commonly. A high retrieval cost may be incurred on unreliable channels even when the requested content is in the nearby cache. To solve the issues mentioned above, we jointly optimize the service scheduling policy and the content caching policy in this paper. We propose a maximal reward priority (MRP) policy to serve user requests, and a collaborative multi-agent actor critic (CMA-AC) policy to update the local cache. Simulation results show that the proposed MRP policy outperforms the shortest distance priority (SDP) policy [4]. And the proposed CMA-AC policy obtains a better performance compared with a distributed multi-agent deep Q-network (DMA-DQN) policy, especially when the number of contents and the capacity of local cache are large. Furthermore, the proposed CMA-AC policy is robust.