Messages In Network Research Articles

Routing algorithm based on triangular fuzzy layer model and multi‐layer clustering for opportunistic network

With the development of 5G network and big data and the popularity of mobile intelligent devices, the opportunistic social network has been further developed. At present, several existing routing algorithms based on node similarity use the context information of the node to select the best relay node. However, most opportunistic social algorithms only consider the social properties of nodes and ignore the importance of the similarity of the moving trajectories of the nodes. The transmission opportunity of messages in the opportunity social network is generated by the movement of the nodes, so this feature must betaken into account in the designing of the routing algorithm. Therefore, this study proposes a routing algorithm based on the triangular fuzzy layer model and multi-layer clustering for the opportunistic social network. In this study, the authors use the fuzzy analytic hierarchy process model to analyse the social similarity and trajectory similarity to determine the best message transmission node. This study compares the other four opportunistic social network routing algorithms in the simulation environment. In general, among the five routing algorithms, the transmission rate of the TFMC algorithm is the best. The average end-to-end delay and average network overhead are also the lowest.

Animating inter-organisational resilience communication: A participatory social network analysis of water governance in the UK

Resilience as a concept and resilience assessment as a practice are being explored across a range of social, ecological and technical systems. In this paper, we propose a new method and visualisation approach for interrogating the communication of resilience within organisational networks, using participatory social network analysis and message passing. Through an examination of the UK water sector organisational network, represented by multiple co-produced network graphs, we identify organisations having a key role in the communication of resilience regulatory and evidence messages, as well as highlighting the potential role of complexity tools in strategy formulation. Animations are presented showing the dynamics of resilience communication, which is discussed. Reflections on the use of participatory social network analysis are explored, as the method opens new doors to potentially examine how network changes could alter communication. Key insights highlight that perceived responsibilities for resilience in the UK water sector rest with a small core of organisations; water customers play a limited role in the two-way communication of resilience and water sector organisations do not communicate widely on resilience with other sectors (such as energy). Additionally, who an organisations’ neighbours are and what catalyses a message to be passed are important in determining how quickly messages spread. Results lead to a recommendation that high level governmental and policy organisations should engage to a greater extent with new resilience knowledge and consider the use of complexity tools in policy making. Policy in relation to resilience is not keeping pace with such knowledge, limiting the communication and learning of organisations who ardently follow policy and regulation. For inter-organisational cooperation to make a difference to water governance, such organisations need to be encouraged to communicate and embed the latest approaches in relation to resilience and complexity thinking and practice.

MultiFuzz: A Coverage-Based Multiparty-Protocol Fuzzer for IoT Publish/Subscribe Protocols.

The publish/subscribe model has gained prominence in the Internet of things (IoT) network, and both Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) support it. However, existing coverage-based fuzzers may miss some paths when fuzzing such publish/subscribe protocols, because they implicitly assume that there are only two parties in a protocol, which is not true now since there are three parties, i.e., the publisher, the subscriber and the broker. In this paper, we propose MultiFuzz, a new coverage-based multiparty-protocol fuzzer. First, it embeds multiple-connection information in a single input. Second, it uses a message mutation algorithm to stimulate protocol state transitions, without the need of protocol specifications. Third, it uses a new desockmulti module to feed the network messages into the program under test. desockmulti is similar to desock (Preeny), a tool widely used by the community, but it is specially designed for fuzzing and is 10x faster. We implement MultiFuzz based on AFL, and use it to fuzz two popular projects Eclipse Mosquitto and libCoAP. We reported discovered problems to the projects. In addition, we compare MultiFuzz with AFL and two state-of-the-art fuzzers, MOPT and AFLNET, and find it discovering more paths and crashes.

Upaya Meningkatkan Kepekaan Sosial Melalui Layanan Konseling Kelompok Dengan Teknik Modeling pada MTs Al-Ikhwan Banjarmasin

The use of media in providing counseling services greatly affects the skills of counselors in conducting counseling through virtual internet media. The development of communication technology in the era of 4.0 makes counselors more familiar with, utilizing and applying counseling media virtually via the internet. The development of communication technology requires counselors to innovate, especially in providing e-counseling services as a forum for counselors to provide alternative solutions to problems faced by counselees. This research method is descriptive qualitative research, the source of this research data comes from document studies in the form of books and previous research which is used as a source of data that supports research. The results of this study indicate that online counseling is in the form of virtual counseling technology media, namely: websites, telephones or cellphones, email, video conferencing, chat, instant messaging, computers and other social media networks. The ethics that must be considered by online counselors are how to establish good relationships via the internet, confidentiality aspects in the implementation of counseling, legal aspects in telecommunications via the internet and licensing. Thus online counselors are required to work professionally by paying attention to ethics in the implementation of online counseling.

Age of Information of One-Hop Broadcast Communications in a CSMA Network

We consider a network of agents that send periodic updates to their neighbors. A trade-off between load on the shared communication channel and data timeliness is obtained by looking at the Age of Information (AoI) metric. We develop a model of a Carrier-Sense Multiple Access (CSMA) network with partial sensing, to calculate the AoI of one-hop broadcast messages exchanged among the agents. The model is applied to beacon messages in a vehicular network to gain insight into the impact of system parameters.

Batch-Assisted Verification Scheme for Reducing Message Verification Delay of the Vehicular Ad Hoc Networks

In terms of preventing traffic accidents, improving traffic efficiency and ensuring personal safety, the research on vehicular ad hoc networks (VANETs) is of great significance. Message authentication is an important security foundation for VANETs. With the rapid growth of the number of access terminals, the existing computing power of the VANETs will not be able to meet the fast message verification service load of large-scale dynamic networks. This article proposes a novel distributed collaborative authentication method. By selecting a reasonable number of assistance verification terminals in the VANETs system and cooperating with the roadside unit (RSU) to jointly undertake the task of network message verification, the purpose is to reduce the verification delay and achieve fast message verification. The simulation results show that in a large-scale connected vehicle with a large number of system terminals, the system message verification delay of our scheme is shortened to one tenth of the centralized verification system message verification delay.

Identification of Fictitious Messages in Social Network using E-Hits and Newsapi

Social network has become a primary resource for users to send and receive the foremost up-to-date data and trend the present events. Currently, most of the social network contains the fictional content that was created by the influential spreaders wherever the message originality and therefore the spreader identity cannot be found which affects the end users. The proposed models to discover fictitious messages are verifying the contextual integrity with the trained classifier using large datasets. But the problem lies in updating of datasets with the recent or trending events from trusted sources in a regular interval. In the existing model, Hypertext-Induced Topic Search (HITS) method has been used for rating posts based on hub score and authority score. The hub score is calculated based on how many posts are posted or liked or tagged by the user and authority score is calculated based on how many users liked or tagged a post. If the user who ranks high in hub score tries to trend the low ranked post in authority score, the user will be marked as spreader. But the problem lies in the identification and verification of the posts that ranks in authority score. In our proposed system, we have enhanced the HITS algorithm by adding a third mechanism called top score which assigns weightage for every post based on the time they have posted. The time and content of the post has been verified by the integrated new model NewsAPI. Based on the three scores, the posts are filtered and matched with the news collected from NewsAPI. The news or posts that have not been matched either with the context or with the time will be marked as fictitious.

Competition for Attention in Online Social Networks: Implications for Seeding Strategies

Many firms try to leverage consumers’ interactions on social platforms as part of their communication strategies. However, information on online social networks only propagates if it receives consumers’ attention. This paper proposes a seeding strategy to maximize information propagation while accounting for competition for attention. The theory of exchange networks serves as the framework for identifying the optimal seeding strategy and recommends seeding people that have many friends, who, in turn, have only a few friends. There is little competition for the attention of those seeds’ friends, and these friends are therefore responsive to the messages they receive. Using a game-theoretic model, we show that it is optimal to seed people with the highest Bonacich centrality. Importantly, in contrast to previous seeding literature that assumed a fixed and nonnegative connectivity parameter of the Bonacich measure, we demonstrate that this connectivity parameter is negative and needs to be estimated. Two independent empirical validations using a total of 34 social media campaigns on two different large online social networks show that the proposed seeding strategy can substantially increase a campaign’s reach. The second study uses the activity network of messages exchanged to confirm that the effects are driven by competition for attention. This paper was accepted by Anandhi Bharadwaj, information systems.

Performance analysis of handover delay and buffer capacity in mobile OpenFlow‐based networks

SummarySoftware‐defined networking (SDN) is a network concept that brings significant benefits for the mobile cellular operators. In an SDN‐based core network, the average service time of an OpenFlow switch is highly influenced by the total capacity and type of the output buffer, which is used for temporary storage of the incoming packets. In this work, the main goal is to model the handover delay due to the exchange of OpenFlow‐related messages in mobile SDN networks. The handover delay is defined as the overall delay experienced by the mobile node within the handover procedure, when reestablishing an ongoing session from the switch in the source eNodeB to the switch in the destination eNodeB. We propose a new analytical model, and we compare two systems with different SDN switch designs that model a continuous time Markov process by using quasi‐birth–death processes: (1) single shared buffer without priority (model SFB), used for all output ports for both control and user traffic, and (2) two isolated buffers with priority (model priority finite buffering [PFB]), one for control and the other for user plane traffic, where the control traffic is always prioritized. The two proposed systems are compared in terms of total handover delay and minimal buffer capacity needed to satisfy a certain packet error ratio imposed by the link. The mathematical modeling is verified via extensive simulations. In terms of handover delay, the results show that the model PFB outperforms the model SFB, especially for networks with high number of users and high probability of packet‐in messages. As for the buffer dimensioning analysis, for lower arrival rates, low number of users, and low probability of packet‐in messages, the model SFB has the advantage of requiring a smaller buffer size.

Modeling of OpenFlow-related handover messages in mobile networks

Software defined networking (SDN) and its most popular southbound implementation OpenFlow (OF) are already greatly exploited in the existing mobile cellular networks as part of data centers and mobile core networks. Due to user’s mobility, it is of upmost importance for the operators to provide the shortest possible interruption when the mobile users are performing the procedure of handover. In this work, we proposed a novel analytical approach to model the OF-related handover messages exchanged between the OF-switches and the SDN controller. We modeled two different OF-switch implementations and we compared the results: (1) single shared buffer used for the control and data plane; (2) two priority buffers, where the data plane packets are served only when there are no packets to be processed in the control plane. We numerically evaluated the two systems and we validated the model by using simulations. The obtained results clearly point that although the priority buffering increased the complexity, it effectively provided the shortest handover delay. Therefore, the priority buffering should be the preferred mechanism for mobile networks.

Traffic Analysis of a Congested and Uncongested Network in a Sequential Server Model

The efficient flow of messages in a communication network is crucial in today’s dynamic environment. These networks are designed to transmit messages in the shortest amount of time. The source sends the messages to the destination through single or multiple servers. Each server contains a buffer that queues the incoming messages when it is busy. This study analyzed the traffic behavior of uncongested and congested wired communication networks for limited and unlimited queue sizes in multiserver configurations with a sequential server model. The performance of the network was measured using three cases: varying the packet length, adding an extra link, and with a broken link connecting the two servers. The performance of the wired communication networks for these three cases was measured based on packet drop rate, throughput, and average end-to-end delay using the OMNeT++ network simulator. Limited and unlimited queue sizes for a sequential server in the network were implemented and simulated to measure the interarrival rate and packet length for optimum performance. For various interarrival rates, the optimum throughput was measured for different queue sizes. The performance with a broken link or the addition of an extra link was assessed and compared with the sequential server model.

The distribution of age-of-information performance measures for message processing systems

The idea behind the recently introduced “age-of-information” performance measure of a network message processing system is that it indicates our knowledge regarding the “freshness” of the most recent piece of information that can be used as a criterion for real-time control. In this foundational paper, we examine two such measures, one that has been extensively studied in the recent literature and a new one that could be more relevant from the point of view of the processor. Considering these measures as stochastic processes in a stationary environment (defined by the arrival processes, message processing times and admission controls in bufferless systems), we characterize their distributions using the Palm inversion formula. Under renewal assumptions, we derive explicit solutions for their Laplace transforms and show some interesting decomposition properties. Previous work has mostly focused on computation of expectations in very particular cases. We argue that using bufferless or very small buffer systems is best and support this by simulation. We also pose some open problems including assessment of enqueueing policies that may be better in cases where one wishes to minimize more general functionals of the age-of-information measures.

A Comprehensive Review on IoT Protocols’ Features in Smart Grid Communication

Since the smart grid deals with a large mass of data and critical missions, it requires ubiquitous, reliable, and real-time communication. The Internet of Things (IoT) technology, which has the potential of connecting all objects over the globe through the Internet, excels in providing robust information transmission infrastructure in the smart grid. There are a multitude of possible protocols, standards, and configurations for communication in the smart grid. A commonly applied communication standard IEC 61850 recommends the use of Manufacturing Message Specification (MMS) protocol for communication in Local Area Network (LAN) and eXtensible Messaging and Presence Protocol (XMPP) in Wide Area Network (WAN). However, a plethora of research on this topic compares the behavior of other IoT protocols and standard recommendations in the smart grid. On the other hand, the sky-rocketing penetration of Renewable Energy Sources (RES), especially in the form of micro grid, transformed the central control structure of the smart grid into a distributed style called Multi-Agent Systems (MAS). This new approach defined new communication requirements and more particular IoT protocol characteristic requirements. However, a limited number of the existing studies have considered IoT protocol characteristic requirements of the smart grid and its new control structures. In this paper, we initially investigate the communication requirements of the smart grid and introduce all IoT protocols and their specifications. We analyze IoT protocol characteristics and performances in the smart grid through literature review based on the smart grid communication requirements. In this approach, we highlight weak points of these practices making them fail to acquire the holistic guidelines in utilizing proper IoT protocol that can meet the smart grid environment interaction requirements. Using the existing facilities, the public Internet, we follow the arrangement of cost-effective high penetration communication requirements for new structures of the smart grid, i.e., the MAS and multi-micro grid. In this case, we consider IoT protocol Quality of Services (QoS) requirements, especially in the case of security and reliability, to satisfy stakeholders, namely utilities and prosumers. Addressing effective elements in applying IoT in the smart grid’s future trends is another contribution to this paper.

Online reverse engineering of CAN data

These days, most vehicles are equipped with the Controller Area Network (CAN) messaging system. This system enable numerous on-board sensors to share useful data with each other. Clearly, this data can be of high value for other applications within Internet of Things. However, the interpretation of that data is devious due to the CAN protocol. Hence, to give sense to the acquired data, reverse engineering is needed to provide insights of the sensor data of the vehicle. In terms of reverse engineering, this is already an ongoing topic in research. However, no methods already exist to perform this reverse engineering process in an online way. Therefore, this paper presents novel methods to detect and identify signals, both for continuous and discrete signals. The reverse engineering process for continuous signals deals with search space reduction and evaluating correlations between requested signals and obtained references. This paper also introduces a new methodology to generate reference signals by transferring knowledge of different vehicles. In terms of reverse engineering discrete signals, this paper presents a novel method that utilises the user during the process. The results show that our presented methods have a high potential value, but generalisation over a wider variety of vehicles and situations is needed. However, this paper paves a way to a more scalable and usable solution for reverse engineering in future applications.

Integrating Security in Resource-Constrained Cyber-Physical Systems

Defense mechanisms against network-level attacks are commonly based on the use of cryptographic techniques, such as lengthy message authentication codes (MAC) that provide data integrity guarantees. However, such mechanisms require significant resources (both computational and network bandwidth), which prevents their continuous use in resource-constrained cyber-physical systems (CPS). Recently, it was shown how physical properties of controlled systems can be exploited to relax these stringent requirements for systems where sensor measurements and actuator commands are transmitted over a potentially compromised network; specifically, that merely intermittent use of data authentication (i.e., at occasional time points during system execution), can still provide strong Quality-of-Control (QoC) guarantees even in the presence of false-data injection attacks, such as Man-in-the-Middle (MitM) attacks. Consequently, in this work, we focus on integrating security into existing resource-constrained CPS, in order to protect against MitM attacks on a system where a set of control tasks communicates over a real-time network with system sensors and actuators. We introduce a design-time methodology that incorporates requirements for QoC in the presence of attacks into end-to-end timing constraints for real-time control transactions, which include data acquisition and authentication, real-time network messages, and control tasks. This allows us to formulate a mixed integer linear programming-based method for direct synthesis of schedulable tasks and message parameters (i.e., deadlines and offsets) that do not violate timing requirements for the already deployed controllers, while adding a sufficient level of protection against network-based attacks; specifically, the synthesis method also provides suitable intermittent authentication policies that ensure the desired QoC levels under attack. To additionally reduce the security-related bandwidth overhead, we propose the use of cumulative message authentication at time instances when the integrity of messages from subsets of sensors should be ensured. Furthermore, we introduce a method for the opportunistic use of the remaining resources to further improve the overall QoC guarantees while ensuring system (i.e., task and message) schedulability. Finally, we demonstrate applicability and scalability of our methodology on synthetic automotive systems as well as a real-world automotive case-study.

An Efficient Delay Tolerant Networks Routing Protocol for Information-Centric Networking

Delay tolerant networks (DTN) is a good candidate for delivering information-centric networking (ICN) messages in fragmented networks due to disaster. In order to efficiently deliver ICN messages in DTN, the characteristics of multiple requester nodes for the same content and multiple provider nodes for the same request should be used efficiently. In this paper, we propose an efficient DTN routing protocol for ICN. In the proposed protocol, requester information for request packet, which is called an Interest in ICN, is shared by exchanging status table with requested Data ID, requester ID, and satisfaction flag, where satisfaction flag is defined to show the delivery status of Data, so that unnecessary forwarding of Data is avoided. Data is forwarded to a more probable node by comparing average delivery predictability to a set of requesters. Performance of the proposed protocol was evaluated using simulation from the aspect of Data delivery probability and Data overhead, for varying buffer sizes, number of relay nodes, and time-to-live (TTL) of Data. The results show that the proposed protocol has better Data delivery probability, compared to content distribution and retrieval framework in disaster networks for public protection (CIDOR) and opportunistic forwarding (OF) protocols, although there is a tradeoff from the aspect of Data overhead for varying buffer sizes and number of relay nodes.

Empirical Models for the Realistic Generation of Cooperative Awareness Messages in Vehicular Networks

Most V2X (Vehicle-to-Everything) applications rely on broadcasting awareness messages known as CAM (Cooperative Awareness Messages) in ETSI or BSM (Basic Safety Message) in SAE standards. A large number of studies have been devoted to guarantee their reliable transmission. However, to date, the studies are generally based on simplified data traffic models that generate awareness messages at periodic intervals or with a constant message size. These models do not accurately represent the real generation of CAM messages that follow specific mobility-based rules. Using simplified and unrealistic traffic models can significantly impact the results and validity of the studies, and hence accurate models for the generation of awareness messages are necessary. This paper proposes the first set of models that can realistically generate CAM messages. The models have been created from real traces collected by two car manufacturers in urban, sub-urban and highway test drives. The models are based on mth order Markov sources, and model the size of CAMs and the time interval between CAMs. The models are openly provided to the community and can be easily integrated into any simulator.

Evaluating Public Anxiety for Topic-Based Communities in Social Networks

Although individual anxiety evaluation has been well studied, there is still not much work on evaluating public anxiety of groups, especially in the form of communities on social networks, which can be leveraged to detect mental healthness of a society. However, we cannot simply average individual anxiety scores to evaluate a community's public anxiety, because following factors should be considered: (1) impacts from interpersonal relations on each individual group member's anxiety levels (the <inline-formula><tex-math notation="LaTeX">${\tt Structural}$</tex-math></inline-formula> component); (2) topic-based discussions which reflect a community's anxiety status (the <inline-formula><tex-math notation="LaTeX">${\tt Topical}$</tex-math></inline-formula> component). In this paper, we initiate the study of evaluating public anxiety of Topic-based Social Network Communities ( <inline-formula><tex-math notation="LaTeX">$\textsc {TSNC}$</tex-math></inline-formula> ). We propose an evaluation framework to project the anxiety level of a <inline-formula><tex-math notation="LaTeX">$\textsc {TSNC}$</tex-math></inline-formula> into a score in the [0,1] range. We devise a cascading model to dynamically compute the individual anxiety scores using the <inline-formula><tex-math notation="LaTeX">${\tt Structural}$</tex-math></inline-formula> influence. We design a probabilistic model to measure anxiety score of social network messages using a generalized user, and compose a tree structure ( <inline-formula><tex-math notation="LaTeX">${\tt MC}$</tex-math></inline-formula> - <inline-formula><tex-math notation="LaTeX">${\tt Tree}$</tex-math></inline-formula> ) to effectively compute the anxiety score of a <inline-formula><tex-math notation="LaTeX">$\textsc {TSNC}$</tex-math></inline-formula> from the <inline-formula><tex-math notation="LaTeX">${\tt Topical}$</tex-math></inline-formula> aspect. For large communities, to avoid expensive real-time computing, we use a small sample to compute the public anxiety within given confidence interval. The effectiveness of our model are verified by precision and recall in an empirical study on real-world Weibo and Twitter data sets.

Risk Assessment of Smart Substation Relay Protection System Based on Markov Model and Risk Transfer Network

To effectively guarantee a secure and stable operation of a smart substation, it is essential to develop a relay protection system considering the real-time online operation state evaluation and the risk assessment of that substation. In this paper, based on action data, defect data, and network message information of the system protection device (PD), a Markov model-based operation state evaluation method is firstly proposed for each device in the relay protection system (RPS). Then, the risk assessment of RPS in the smart substation is carried out by utilizing the risk transfer network. Finally, to highly verify the usefulness and the effectiveness of the proposed method, a case study of a typical 220 kV substation is provided. It follows from the case study that the developed method can achieve a better improvement for the maintenance plan of the smart substation.

Automated classification of social network messages into Smart Cities dimensions

A Smart City can be defined as a high-tech city with several public and private services capable to strategically solve (or mitigate) problems normally generated by rapid urbanization. Different models of indicators have been developed to follow cities’ evolution to become a Smart City. An example of such model is the standard 37120 from the International Organization for Standardization (ISO) that proposes a set of dimensions and indicators (e.g. Transportation, Recreation, Solid Waste) for services and quality of life for sustainable cities and communities. It has been common to find official social network profiles of organizations and governmental entities related to the services they provide or are responsible for (water, waste, transportation, cultural events, etc.) and that are used by citizens as a gateway to directly interact and communicate their complains and problems about those services. The present paper proposes to apply machine learning algorithms over the urban data generated by social networks in order to create classifiers to automatically categorize citizens messages according to the different cities services dimensions. For that, two distinct text datasets in Portuguese were collected from two social networks: Twitter (1,950 tweets) and Colab.re (65,066 posts). The texts were mapped according to the different ISO 37120 categories, preprocessed and mined through the use of 8 algorithms implemented in Scikit-Learn. Initial results pointed out the feasibility of the proposal with models achieving average F1-measures around 55% for F1-macro and 78% for F1-micro when using Linear Vector Classification, Logistic Regression, Decision Tree and Complement Naive Bayes. However, as the datasets were highly unbalanced, the performances of the models vary significantly for each ISO category, with the best results occurring for Wastewater, Water & Sanitation, Energy and Transportation. The classifiers generated here can be integrated on a number of different city services and systems such as: governmental support decision systems, customer complain systems, communities dashboards, police offices, transportation’s companies, cultural producers, environmental agencies, and recyclers’ companies.