Node Failure Rate Research Articles

Advanced network design for 6G: Leveraging graph theory and slicing for edge stability

The advent of 6 G networks will emphasize AR/VR-based tactile internet and touch-enabled services, requiring solutions to address latency and reliability issues in tactile data perception, particularly in edge networking. This article highlights the critical role of graph theory in improving network design for both symmetric and randomly deployed networks, and it emphasizes the importance of network slicing in managing densely connected edge networks. These networks typically consist of numerous edge devices that enable data transfer to higher layers, enhancing connectivity and ensuring network stability within a confined range. The paper compares the accuracy of conventional networks before and after implementing network slicing, with the goal of increasing reliability by dividing the edge network into segments, thereby reducing computation time. The study proposes a method for optimal node segregation and path determination in edge networks using both uniform and random network slicing. Network performance is assessed using metrics such as computation time and node failure rate. The paper concludes that network slicing is the most effective design approach for touch technology interfaces within 6 G and IoT frameworks.

Evolution and stability of liner shipping networks in Northeast Asia from 2018 to 2022

Ports are severely challenged by the uncertainty of the transportation environment. To evaluate the stability of maritime transportation network in Northeast Asia under port disruption, a network stability analysis model based on node failure rate that considers static and structural, dynamic and functional is proposed in this paper. In this model, the stability of the maritime transportation network is redefined. Based on complex network theory, the statistical topological parameters and evolution of the network are quantitatively analyzed. The active response and passive adaptation process of the maritime transportation network to the failure rate of the port are analyzed. The evaluation results illustrate that the initial stability of the port is proportional to the non-redundant connections and independence of the port. Network location advantages profoundly affect the probability of port failures. The diffusion of port failures in maritime transportation is phased, and the network is adaptive to port disruptions and has high stability. These results contribute to better planning of maritime transportation routes and strategies for port calls by strategic planners of shipping companies.

The cascade failure model under ecological network is effective for quantifying the resilience of urban regions

Human activities and natural disasters degrade urban ecosystems and cause ecological fragmentation at regional scale. It is therefore necessary to create or rehabilitate useful linkages between ecological spaces. Although ecosystem resilience is receiving increasing attention, most studies focus on the spatiotemporal changes of alternative indicators of ecosystem resilience, without considering the changes in the structure and function of internal ecological nodes. Therefore, this study presents a novel research framework that uses cascade failure model based on the ecological network (EN) to evaluate the resilience of typical urban areas. The framework combines “importance-vulnerability” scored ecological sources identification with minimum cumulative resistance simulation to quantitatively characterize the urban region as an EN and assesses the resilience of the urban EN using a capacity-load cascade failure model. The framework was tested in the Xi'an metropolitan region in China resulted in the regional EN with 191 nodes and 571 edges. It was found that the EN of the Xi'an metropolitan region was relatively stable. The network will completely break down only when the node failure rate exceeds 85 %. The framework we propose offers a novel and powerful approach for policymakers to plan for the conservation and development of ecological infrastructure and land uses in urban region context.

An Analysis of Hierarchical Routing Strategy with Advanced Additional Sensors in WSNs

Two kinds of sensors will be discussed in some sort of wireless sensor networks (WSNs). One is named a normal sensor (called A_nodes) with fixed initial energy, which can get perception data from the surrounding environment and have functions of storage and forwarding. The other is named relay sensor (called B_node) with sufficient energy, which only can store data and forward data. Cluster heads (called A_heads) are chosen among A_nodes by probability mode to create clusters first. Local adjustments would be done inter-cluster. Then the sink is selected as the root and a backbone shortest path tree with hops limited is built dynamically from A_heads, B_Nodes and sink. Inside the backbone shortest path aggregation tree, two steps are done. The first step, select some B_node as cluster head (denoted as B_node) and make local adjustment intra-clusters if it is possible. The second step, adjust the shortest path aggregation tree. By using both particle swarm optimization (PSO) and ant colony optimization (ACO), a traveling salesman problem (TSP) cycle with shorter path length is obtained (this method is noted as TSP_PSO_ACO). This TSP cycle consists of all nodes in the aggregation backbone tree. Along this cycle, energy is offered to nodes except sink. The above strategy would be discussed for its feasibility and time complexity. The experimental results imply that the energy consumption is reduced by using local adjustment. The relative failure rate of nodes can be reduced in the later stage of WSN survival. Offering energy to a small number of nodes several times has no obvious impact on the overall energy consumption and survival time of WSN. The case with some small-sized obstacles in WSN area is also discussed. There are little affections on TSP cycles both from results on theoretical analysis and simulation if there are some obstacles with small size in WSN area.

Robustness of the International Wheat Trade Network

Grain is the material basis for human survival and development, wheat is one of the three significant grains, and the robustness of the wheat trade has seriously affected world grain security. In the paper, we analyze the robustness of the International Wheat Trade Network (IWTN) from three perspectives: global, regional, and national. We quantify the topological properties and evolution characteristics of IWTN from 1987 to 2020, and analyze the stability of IWTN using random attacks and target attacks. The import satisfaction of major wheat trading countries and trade communities is quantified through import stability indicators. Firstly, the results show that IWTN satisfies the scale-free property and that global wheat trade transactions continue to increase. Secondly, IWTN under random attack forms a “convex” curve regarding network efficiency. It shows that IWTN has better resistance to external shocks, and higher robustness. However, under the targeted attack, the network collapses when the node failure rate reaches 40%. Regardless of the attack mode, the decreasing trend of network efficiency and connectivity is the same in different years as the number of failed nodes gradually increases, and no year shows outstanding stability. Thirdly, different communities in the wheat trade are more satisfied with the wheat imports of their internal countries, and most of the wheat trade occurs within the same trading community. Fourthly, among the top five global wheat importers in 2020, Italy and Turkey have diversified sources of imports, but trade imports are relatively concentrated. In contrast, China, Egypt and Indonesia have relatively balanced wheat trade imports from their respective trading countries and are less at risk of being affected in the event of supply risks.

A QoS-Aware Energy-Efficient Chimp Optimization Routing Protocol with Efficient Sensor Node Deployment Strategy in Underwater Acoustic Sensor Network

As an extension of wireless sensor networks in the underwater environment, Underwater Acoustic Sensor Networks (UASNs) have led to a broad consideration of academicians. One of the problems that lower UWSN effectiveness in terms of network lifespan is premature energy depletion. It might be caused by the network nodes using different amounts of energy. In UASNs, the effectiveness and dependability of data transfer remain so adverse because of the intricate underwater environment in diverse ocean applications like surveilling atypical submarine oil pipelines. Inspired by the significance of UASNs’ quality of service in several implementations, this study proffers a metaheuristic optimization algorithm (AG) called Chimp Optimization-based Routing Protocol (CH-ORP) for UASNs obtaining intricate features of underwater (UW) medium into concern like 3D changing topology, high propagation delay, node mobility, and density, and, also, cluster head nodes’ rotation mechanism. Initially, the entire network (NW) paradigm has been considered as a three-dimensional cube out of a grid point of view, and the three-dimensional cube has been split into several little cubes by employing Delaunay Triangulation. The optimization has been carried out for lessening node failure rate and NW energy consumption rate by ideally placing the sensor nodes in UW acoustic communication. The NW topology’s steadiness has been assured by the AG, and this optimizes the node redeployment scheme by computing the fitness function for all nodes. The proffered AG’s simulation substantiations have been performed for exhibiting the CH-ORP’s efficiency that executes finer when compared to the advanced methodologies concerning energy efficiency, reliability, and end-to-end delay. It has been found that the proposed Ch-ORP achieves 698 packets received with 28% of energy consumption, 156-sec Network delay, 257 packet loss, 97.23% of PDR, and 1256 Mbps of Network throughput.

Optimize and analysis of drilling PMSM using hybrid technique based on BN, FFT, FCE, and FMA for risk assessment

A failure risk assessment must be carried out and potential drilling equipment failure risks must be promptly addressed in order to prevent drilling fluid pollution during offshore oil drilling. The qualitative, comprehensive, and quantitative failure risks for Drilling Permanent Magnetic Synchronous Motors (DPMSM) are examined in this article using a hybrid methodology. First, the Drilling PMSM using Failure Mode Analysis (FMA) method is combined with the Risk Matrix (RM) approach to analyse the risk levels of risk factors individually. Next, the Borda number is introduced to compare the risk levels exactly. To execute a Fuzzy Comprehensive Evaluation (FCE) of the system failure risk, a fuzzy relation matrix of risk factors is generated, and the weight of each risk component is calculated using importance analysis. The failure rate is then determined using fuzzy inference, and the Fault Tree (FT) is then built based on the risk variables. Fault tree analysis is used to compute the system failure rate, and the significance of the bottom event is evaluated. The Bayesian network (BN) is used to depict the Fuzzy Fault Tree (FFT) analysis. By utilizing Bayesian forward causal inference and reverse diagnostic inference to calculate the leaf node failure rate and root node posterior probability, the system’s weak points and potential failure causes are determined.

Dynamic Network Topology Portrait for Digital Twin Optical Network

Digital twin (DT) as one promising technology has been introduced in optical networks, whose role is to achieve interactive functions and intelligent control by building a bridge between physical space and digital space. In this paper, a multifactor-associated network topology portrait (NTP) scheme is proposed to draw a dynamic, real-time, and comprehensive topology representation for DT optical network (DTON). Multiple parameters from nodes and links are jointly evaluated, including link distance, link loss, optical signal-to-noise ratio, bandwidth utilization rate, load capacity, node failure rate, and link failure rate, involving both network layer and physical layer. Based on the NTP, the performance of dynamic routing computation combined with six different routing algorithms is studied, Here, the time for routing computation is sacrificed a little bit in exchange for significant improvements in outage probability, outage latency, and the number of service requests.

Optimized Resource Allocation in IoT Using Fuzzy Logic and Bio-Inspired Algorithms

IoT smart devices are a confluence of microprocessors, sensors, power source and transceiver modules to effectively sense, communicate and transfer data. Energy efficiency is a key governing value of the network performance of smart devices in distributed IoT networks. Low and discrete power and limited amount of memory and finite number of resources form some major bottlenecks in the workflow. Dynamic load balancing, reliability and flexibility are heavily relied upon by cloud computing for its accessibility. Resources are dynamically provided to the end client in an as-come on-demand fashion with the global network that is the Internet. Proportionally the need for services is increasing at a rate that is astonishing compared to any other forms of development. Load balancing seems a major challenge faced due to the architecture and the modular nature of our cloud environment. Loads need to be distributed dynamically to all the nodes. In this paper, we have introduced a technique that combines fuzzy logic with various nature inspired algorithms—grey wolf algorithm and firefly algorithm to effectively balance the load in a network of IoT devices. The performances of various nature inspired algorithms are compared with a brute force approach based on energy efficiency, network lifetime maximization, node failure rate and packet delivery ratio.

Research on Communication Stability of Inter-Cannonball Network Based on OPNET

In modern warfare, achieving strikes against military targets commonly involves utilizing methods such as fire coverage and missile precision guidance. While effective, fire coverage requires significant ammunition support, and missiles can be costly. Therefore, an intelligent strike solution can be an effective way to address these challenges. The inter-cannonball wireless communication network provides a solid foundation for inter-cannonball networking and joint strikes. The synergy improves the strike’s range and precision, ensuring own safety and destroying the enemy’s core with success. In this paper, the reliability of inter-cannonball group communication is studied. The vast array of activities and short striking distance of cannonballs make wireless networking between cannonballs a technological challenge. For this unique communication environment, the network of cannonballs is discussed, the self-organizing structure model of the network is proposed, the corresponding node topology is established, the protocol framework of inter-cannonball communication is presented, and the simulation parameters of the communication network are set. On this premise, discrete event simulation is performed by using the OPNET program to validate the impact of failure rate and node movement speed on the inter-cannonball network communication reliability. And the main performance indices of the inter-cannonball communication system are derived. The simulation results indicate that it can maintain basic communication stability, with wireless LAN delays of less than 100 ms, even when the node failure rate reaches 20%. The simulation verification method, on the other hand, overcomes the limitations of the real environment, optimizes the design phase, reduces research costs, and accelerates the development of intelligent cannonballs.

Data-Driven Application-Oriented Reliability Model of a High-Performance Computing System

Reliability analysis and performance evaluation are complementary methods to quantify nonfunctional aspects of a system. However, a range of factors such as concurrency and heterogeneity quickly exacerbate the state-space explosion problem when attempting detailed system-level modeling and simulation of high-performance computing (HPC) systems. To overcome these impediments to modeling and analysis, this article develops a hierarchical model of an application that implements checkpointing running in an HPC environment subject to application, network, and system-wide outages. The modeling approach ensures that the number of states is linear in the number of checkpoints and possesses a low constant factor for the number of recovery states most relevant to the external influences contributing to degraded application performance. We illustrate the types of analysis enabled by the model through a series of examples with parameters determined empirically from data logs of the Blue Waters supercomputer located at the University of Illinois at Urbana–Champaign. A comprehensive comparative analysis of the model parameters indicates that lowering the failure rate of network nodes would most significantly reduce application downtime. We also discuss how the modeling approach can be used to objectively assess both current and hypothetical future systems to identify competitive designs and enhancements.

A Novel Risk Factor for Para-Aortic Lymph Node Recurrence After Definite Pelvic Radiotherapy in Stage IIIB Cervical Cancer.

Background: Studies determining which patients with International Federation of Gynecology and Obstetrics (FIGO) stage IIIB disease benefit from prophylactic extended-field irradiation (EFRT), which can reduce para-aortic lymph node (PALN) failure rates, are limited. The study was designed to evaluate the value of the controlling nutritional status (CONUT) score as a risk factor for predicting PALN recurrence and identifying potential indications of prophylactic EFRT. Methods: From 2010 to 2015, a retrospective review was conducted among patients with FIGO stage IIIB cervical cancer who were treated with definitive pelvic radiotherapy or concurrent chemoradiotherapy. We analyzed para-aortic lymph node metastasis-free survival (PALNMFS) using Kaplan-Meier curves. Multivariate analyses were performed using Cox regression models. Results: A total of 116 patients with FIGO stage IIIB cervical cancer were included in the study and the median follow-up was 42.2 months (range: 3.5-104.2 months). Multivariate analysis revealed that the CONUT score (HR: 3.141; 95% CI: 2.321-5.436; P < .001) and ≥3 pelvic lymph node metastases (HR: 2.235; 95% CI: 1.428-11.242; P < .001) were independent risk predictors of PALNMFS. Compared with the low CONUT group (score<3), the high CONUT group (score≥3) was associated with a significantly worse 3-year disease-free survival rate (46.9 vs 69.5%, P = .001), a significantly lower 3-year overall survival rate (68.5 vs 79.7%, P = .016) and a significantly lower PALNMFS rate (74.8 vs 96.4%, P < .001). Conclusions: A high CONUT score (score≥3) and ≥3 pelvic metastatic lymph nodes were significant predictors of PALNMFS after pelvic radiation in FIGO stage IIIB cervical cancer patients. Patients with these risk factors might benefit from prophylactic EFRT.

Does the primary tumor site in stage I extranodal natural killer/T-cell lymphoma matter?

The purpose of this study was to investigate whether the primary tumor site in stage I extranodal natural killer/T-cell lymphoma (ENKTCL) had a prognostic value. Between January 2009 and December 2015, 152 stage I ENKTCL patients with primary disease in the nasal cavity and Waldeyer's ring were enrolled for this retrospective study. All patients received extended field intensity-modulated radiotherapy alone without prophylactic cervical node irradiation at a total dose of 50 Gy. In this study, there were 122 patients whose primary tumors were localized in the nasal cavity (NC group), and no adjacent structures were involved. A total of 18 patients had a primary disease involving the nasal cavity and Waldeyer's ring (NC-WR group), and the remaining 12 patients had primary tumors confined to Waldeyer's ring (WR group). We found that there was no significant difference in cervical lymph node failure rates among the NC, NC-WR, and WR groups. In terms of the 5-year overall survival (OS) rates, there was a significant difference among the NC, NC-WR, and WR groups (p=0.004), with the WR group having the worst OS. Multivariate analyses showed that the primary site (p=0.011) and ECOG (Eastern Cooperative Oncology Group) score (p=0.013) were independent prognostic factors for OS. In summary, patients with stage I ENKTCL had a good local control rate with radiotherapy alone and without prophylactic cervical node irradiation (PCNI), regardless of the site of the primary tumor. So, we think PCNI for stage I ENKTCL patients is not necessary. Patients with a primary tumor site located in Waldeyer's ring had the worst prognosis. And combined treatment with radiotherapy and chemotherapy should be considered in patients with primary tumors located outside the nasal cavity.

Research on Distance Teaching System of English Course Based on Wireless Network Technology

The development in technology is taking place with an accelerating pace across the globe. The increasing expansion and advancement in the field of information technology and the modern teaching system provide a technical support for the development of a distance teaching system to learn English courses. Multimedia teaching system of English course based on B/S framework (system 1) and English teaching system based on MVC architecture (system 2) were the two most prominent and widely used approaches for the distance teaching system of English learning courses. These systems comprehensively consider the current English teaching needs, develop the existing architectures, discuss the system architecture and functions, and establish the corresponding development environment. However, the mentioned systems have the problem of high proportion of memory resource consumption and high failure rate of the communicating nodes. In order to reduce the proportion of memory resource consumption and node failure rate of distance teaching system and effectively improve the teaching effect, this study designed a distance teaching system of English course based on wireless network technology. In order to analyze the functionality and stability of the wireless network technology in distance teaching of English course, the server-side and client-side modules of the system are designed. The server side is mainly used to maintain and control the overall functions of the system, while the client side is used to access/request the contents from the server. On this basis, the system software module is designed. The memory consumption results are accounted for under 30%, which is significantly lower than the earlier-mentioned systems, and the node failure rate of the system proposed in this paper does not increase significantly and remains below 4% all the time which indeed is a very low amount of failure rate. The experimental results show that the memory resource consumption ratio and node failure rate of the proposed system are very low, and the application feedback effect is significantly better than the other systems.

Effectual Non-Intrusive Minimum-Process Synchronous Checkpointing Protocol for Mobile Distributed Systems

While dealing with Mobile Distributed systems, we come across some issues like: mobility, low bandwidth of wireless channels and dearth of stable storage on mobile nodes, disconnections, inadequate battery power and high failure rate of mobile nodes. Minimum-process coordinated checkpointing is considered an attractive methodology to introduce fault tolerance in mobile systems transparently. In this paper, we propose a non-blocking coordinated global state compilation algorithm for mobile computing systems, which requires only a minimum number of processes to take permanent recovery points. We reduce the communication complexity as compared to the Cao-Singhal algorithm [4], while keeping the number of useless recovery points unchanged. Finally, the paper presents an optimization technique, which significantly reduces the number of useless recovery points at the cost of minor increase in the communication complexity. In coordinated global state compilation, if a single process fails to take its tentative recovery point; all the recovery point effort is aborted. We try to reduce this effort by taking soft recovery points in the first phase at Mobile Hosts.

RETRACTED: Vulnerability analysis of road network for dangerous goods transportation considering intentional attack: Based on Cellular Automata

• The vulnerability of RNDGT under cascading failure considering intentional attack is analyzed. • The time characteristics of load distribution and node recovery ability are considered. • AD, BD, CD, DD, TD and SLD are selected to study the load re-distribution. • DA, BA and TA are selected to study the vulnerability. • CA based cascading failure model is established. The vulnerability of road network for dangerous goods transportation (RNDGT) under cascading failure considering intentional attack is analyzed. We introduce the time characteristics of load distribution and node recovery ability into previous cascading failure model, subdivide the state of failed node into normal state, partial failure state and complete failure state. Six traffic load distribution strategies including Average Distribution (AD), Betweenness Distribution (BD), Capacity Distribution (CD), Degree Distribution (DD), Tightness Distribution (TD) and Surplus Load Distribution (SLD) are selected to study the load re-distribution of failed nodes. In addition, three kinds of intentional node attack strategies including Degree Attack (DA), Betweenness Attack (BA) and Tightness Attack (TA) are selected to study the impact on the vulnerability. By referring the application of cellular automata applied in epidemic spreading field, we establish a new cascading failure model of RNDGT. The improved maximum connectivity and node failure rate based on node degree are applied to analyze the vulnerability. A case study is conducted by using the RNDGT of Dalian as the background. The previous Motter-Lai model (M-L) is applied as the comparison approach. TA strategy has the least impact on increasing network vulnerability, SLD strategy is the best to reduce network vulnerability.

A distributed fault‐tolerant mechanism for mission‐oriented unmanned aerial vehicle swarms

SummaryUnmanned aerial vehicle (UAV) swarm consists of a number of autonomous and collaborative UAV nodes. The purpose of the research is to address the hypotheses: an efficient centralized resources management scheme should be adopted to meet the mission‐oriented feature of UAV swarms, while a distributed fault‐tolerant mechanism should be adopted to meet the characteristics of complex environment and address the issue of high failure rate of UAV nodes. By using an experimental modeling method, this paper proposes a management model and related mechanisms fitting for UAV swarms with the feature of “centralized decision making and distributed task execution.” The model allows UAV nodes to manage their own resources autonomously and execute centralized decisions accordingly. The advantage of the model is that the master node of a UAV swarm is able to perceive all the resources of the system and the status of all (or some) of the UAVs efficiently; therefore, it provides a supportive environment for the UAV swarm application to make centralized decisions and optimize those decisions. Additionally, this paper proposes a distributed fault‐tolerant model and related mechanisms to address the issue of high failure rate of UAV nodes, as well as the system vulnerability caused by harsh environment. Finally, this study developed a prototype system designed and implemented by OMNeT++ to confirm the truth of the hypotheses. The analysis of the experimental data and simulation results of the prototype validated the feasibility and usability of the distributed fault‐tolerant mechanism and demonstrated its value for the mission‐oriented UAV swarms.

HEPSO: an efficient sensor node redeployment strategy based on hybrid optimization algorithm in UWASN

In Underwater Acoustic Sensor Network (UWASN), node redeployment strategy is utilized to handle the reliable network coverage. The sensors deployed in the underwater are used to intellect the area and collected information is moved to the sink node. Node redeployment strategy is essential for the nodes which are placed outside the monitoring area in UWASN. In this paper, the node redeployment strategy is performed based on the hybrid Emperor Penguin Optimization (EPO) algorithm with Particle Search Algorithm (PSO) for better underwater acoustic communication and the proposed method is named as HEPSO. This hybridization is performed to reduce node failure rate and network energy consumption rate by optimally place the sensor nodes in underwater acoustic communication. The stability of the network topology is guaranteed by this algorithm and it enhances the node redeployment strategy by calculating the fitness function for each and every node. The implementation of the proposed algorithm is carried out by the MATLAB platform. The performance parameters like network coverage rate, network connectivity rate, network lifetime, number of nodes outside monitored space and total movement distance of nodes are evaluated and related with current methods like NRBSCT (Node Redeployment Based on Stratified Connected Tree) and MRNR (Moving Redundancy Nodes Redeployment) strategy.

Importance-Different Charging Scheduling Based on Matroid Theory for Wireless Rechargeable Sensor Networks

Charging scheduling plays a significant role in wireless rechargeable sensor networks (WRSNs), which benefit from stable and reliable energy supplements via wireless charging. This paper proposes an importance-different charging scheduling (IDCS) strategy for improving charging utility as well as reducing the data loss. The unique feature of IDCS is that, it distinguishes nodes by means of different importance of data delivery. The Matroid theory is used to achieve our goals. First, two important factors are determined in the Matroid model, i.e., the deadline of the task and the penalty value of the task. Moreover, a greedy algorithm of task classification is designed to minimize the data loss. All tasks are divided into the early tasks and the delayed tasks, and the node with greater importance and shorter deadline has a higher priority of being included into the early tasks. In addition, a charging sequence adjustment approach is proposed to maximize the charging utility. This approach aims to exchange the sequence of different nodes in the trajectory of the mobile charger for exploring a shorter path. Several simulations verified the effectiveness and advantages of our charging scheduling strategy in terms of the node failure rate and total data loss.

Information Resilience in a Network of Caches With Perturbations

Caching in a network of caches has been widely investigated for improving information/content delivery efficiency (e.g., for reducing content delivery latency, server load and bandwidth utilization). In this work, we look into another dimension of network of caches – enhancing resilience in information dissemination rather than improving delivery efficiency. The underlying premise is that when information is cached at more locations, its availability is increased and thus, in turn, improve information delivery resiliency. This is especially important for networks with perturbations (e.g., node failures). Considering a general network of caches, we present a collaborative caching framework for maximizing the availability of the information. Specifically, we formulate an optimization problem for maximizing the joint utility of caching nodes in serving content requests in perturbed networks. We first solve the centralized version of the problem and then propose a distributed caching algorithm that approximates the centralized solution. We compare our proposal against different caching schemes under a range of parameters, using both real-world and synthetic network topologies. The results show that our algorithm can significantly improve the joint utility of caching nodes. With our distributed caching algorithm, the achieved caching utility is up to five times higher than greedy caching scheme. Furthermore, our scheme is found to be robust against increasing node failure rate, even for networks with a high number of vulnerable nodes.