Message Forwarding Algorithm Research Articles

ML-SLD: A message-level stateless design for cloud-native 5G core network

The Internet of Things (IoTs) has become an essential component of the 5th Generation (5G) network and beyond, accelerating the transition to digital society. The increasing signaling traffic generated by billions of IoT devices has placed significant strain on the 5G Core network (5GC) control plane. To address this issue, the 3rd Generation Partnership Project (3GPP) first proposed a Service-Based Architecture (SBA), intending to create a flexible, scalable, and agile cloud-native 5GC. However, considering the coupling of protocol states and functions, there are still many challenges to fully utilize the benefits of the cloud computing and orchestrate the 5GC in a cloud-native manner. We propose a Message-Level StateLess Design (ML-SLD) to provide a cloud-native 5GC from an architectural standpoint in this paper. Firstly, we propose an innovative mechanism for servitization of the N2 interface to maintain the connection between Radio Access Network (RAN) and the 5GC, avoiding interruptions and dropouts of large-scale user data. Furthermore, we propose an On-demand Message Forwarding (OMF) algorithm to reduce the impact of cloud fluctuations on the performance of cloud-native 5GC. Finally, we create a prototype that is based on the OpenAirInterface (OAI) 5G core network projects, with all Network Functions (NFs) packaged in dockers and deployed in a kubernetes-based cloud environment. Several experiments have been built with UERANSIM and Chaosblade simulation tools. The findings demonstrate the viability and efficiency of our proposed methods.

The Optimization of Classroom Teaching in Colleges and Universities Based on Network Topology

In order to improve the teaching effect of programming courses, this article applies network topology to the construction of programming course teaching platform system and constructs a teaching framework combined with intelligent teaching mode. In addition, this article takes the opportunistic social network composed of mobile smart terminal devices as the application background and briefly introduces the concept, characteristics, and application scenarios of the opportunistic social network. In addition, the typical message forwarding algorithm currently studied in this paper is analyzed. Taking into account the social attributes and forwarding willingness of nodes, in order to increase the message transmission rate and reduce message transmission delay and network overhead, two message transmission strategies are proposed to improve the operating effect of the programming course teaching platform. Finally, this paper verifies the effectiveness of the network topology in the teaching of the algorithm and programming of the intelligent teaching mode through experimental research.

Novel congestion avoidance scheme for Internet of Drones

Internet of Drones (IoDs) is getting growing interest of researchers due to its applicability in wide range of applications for transportation, weather monitoring, emergency monitoring for flood, earth quake, healthcare and road hazards. To update the data about emergency situation, a real-time data sharing is mandatory. However, regular message transmission by various drones may not only overwhelm a central server but it also causes congestion on the network. It is mandatory to reduce messaging cost and congestion. This paper presents a fog-assisted congestion avoidance approach for Smooth Message Dissemination (SMD). We present a message forwarding algorithm for congestion avoidance to select the appropriate next-hop node using layered model. This model is based on various layers having drones. In first phase, it looks for an appropriate drone in a layer near the fog server for message forwarding. In next step, the drone is identified in nearby layers to forward the emergency message to next-hop to further locate the group head as per priority. It is a drone that has less distance towards fog server and inform in its one-hop circle. It can stop forwarding message after delivering it to fog server. Finally, the fog server disseminates information timely towards upper layers for necessary actions for emergency situations. The performance of the proposed approach is validated through extensive simulations using NS 2.35. Results prove the dominance of SMD over counterparts in terms of messaging overhead, packet delivery ratio, throughput, energy consumption and average delay. Proposed SMD improves PDR by 85% and message overhead cost by 91% as compared to counterparts.

Secure and Anonymous Communications Over Delay Tolerant Networks

Today’s society has a fundamental need for security and anonymity. Well suited, real-life scenarios such as whistleblower reports, intelligence service operations, and the ability to communicate within oppressive governments, call for such fundamental needs. The contribution and focus of this paper is the study of anonymous communications in the context of Delay Tolerant Networks (DTNs). Current literature achieves anonymity via mechanisms that are built around the onion routing paradigm which, unfortunately, is vulnerable to malicious nodes. Instead, our work introduces a novel message forwarding algorithm that delivers messages, from source to destination, via a random walk process. As such, our protocol does not list the intermediate nodes along the route’s path and, therefore, enhances significantly the anonymity of the underlying communications. We propose two different approaches for encrypting the exchanged messages. The first one is based solely on public key cryptosystems and is, thus, suitable for short, SMS-style messaging. The second one is a hybrid solution that combines both public and symmetric key cryptography and is targeted towards large multimedia messages, such as images or video. Through extensive simulation experiments, we show that our proposed anonymous routing protocol achieves high message delivery rates, while using modest computational resources on the mobile devices.

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

Delay/Disruption Tolerant Networking-Based Routing for Rural Internet Connectivity (DRINC)

Rural networking connectivity is a very dynamic and attractive research field. Nowadays big IT companies and many governments are working to help connect all these rural, disconnected people to Internet. This paper introduces a new routing algorithm that can bring non-real-time Internet connectivity to rural users. This solution is based on previously tested ideas, especially on Delay/Disruption Tolerant Networking technologies, since they can be used to transmit messages to and from difficult to access sites. It introduces the rural connectivity problem and its context. Then, it shows the proposed solution with its mathematical model used to describe the problem, its proposed heuristic, and its results. The advantage of our solution is that it is a low-cost technology that uses locally available infrastructure to reach even the most remote towns. The mathematical model describes the problem of transmitting messages from a rural, usually disconnected user, to an Internet connected node, through a non-reliable network using estimated delivery probabilities varying through time. The forwarding algorithm uses local knowledge gathered from interactions with other nodes, and it learns which nodes are more likely to connect in the future, and which nodes are more likely to deliver the messages to the destination. Our algorithm achieves an equal or better performance in delivery rate and delay than other well-known routing protocols for the rural scenarios tested. This paper adds more simulation results for the proposed rural scenarios, and it also extends the explanation of the mathematical model and the heuristic algorithm from the conference paper "Delay/Disruption Tolerant Networks Based Message Forwarding Algorithm for Rural Internet Connectivity Applications" [1] (doi: 10.1109/ICCCC. 2016.7496732).

Energy Efficient Forwarding Algorithm in Opportunistic Networks

In opportunistic networks, a successful message transmission between node pairs depends on the message size, the transmission speed and the connection duration time. This paper proposes a new message forwarding algorithm to improve the message delivery ratio and reduce the energy consumption. Previous encounter characteristics between nodes are used to estimate future connection duration time using a three point estimation method. Furthermore, the buffer utilization of nodes is used as a weight for the likelihoods to meet destinations according to the hop count of messages stored in the buffer. The simulation results show that the proposed forwarding algorithm achieves higher delivery ratio and less overhead ratio than the other four popular routing protocols. In addition, the proposed algorithm gains a better average residual energy performance among all the compared protocols.

A Data Age Dependent Broadcast Forwarding Algorithm for Reliable Platooning Applications

We propose a broadcast message forwarding algorithm for V2V communication in a platooning scenario for heavy duty trucks. The algorithm utilizes link information, which is piggybacked on the original data packet, to estimate which nodes are best suited to forward the packet. The aim is to reach all nodes in the platoon with as few forward messages as possible in order to avoid channel congestion. The algorithm is evaluated by simulation using real world V2V measurement data as input. We show that the algorithm performs almost as good as two ETSI standardized forwarding algorithms with respect to keeping the data age for the entire platoon at a low level. But when it comes to keeping the message intensity low, our algorithm outperforms the better of the ETSI algorithms by 35%.

Congestion‐aware message forwarding in delay tolerant networks: a community perspective

SummaryIn delay tolerant networks, most of the existing message forwarding algorithms prefer to deliver messages to the nodes with a higher popularity or centrality in the hope of maximizing the delivery ratio or minimizing the end‐to‐end delay. This forwarding scheme is prone to cause unfair load distribution and further lead to network congestion, overlooked in the previous work. In this paper, we discuss the network congestion from a community perspective and take it into account the design of message forwarding algorithms. We first put forward a novel distributed community detection approach, which could track the evolution of communities. Based on the identified communities, we develop a congestion avoidance mechanism to divert the load away from the congested areas to the alternative custodians and further present a congestion‐aware message forwarding algorithm where messages can avoid being transmitted to the congested nodes. We finally evaluate the effectiveness of distributed community detection and congestion‐aware message forwarding through the extensive real‐trace driven simulations. Copyright © 2015 John Wiley & Sons, Ltd.

CAMF: Context-Aware Message Forwarding in Mobile Social Networks

In mobile social networks (MSN), with the aim of conserving limited resources, egotistic nodes might refuse to forward messages for other nodes. Different from previous work which mainly focuses on promoting cooperation between selfish nodes, we consider it from a more pragmatic perspective in this paper. Be specific, we regard selfishness as a native attribute of a system and allow nodes to exhibit selfish behavior in the process of message forwarding. Apparently, selfishness has a profound influence on routing efficiency, and thus novel mechanisms are necessary to improve routing performance when self-centered nodes are considered. We first put forward a stateless approach to measure encounter opportunities between nodes, and represent forwarding capabilities of nodes by combining the acquired encounter opportunities with node selfishness. We then quantify receiving capabilities of nodes based on their available buffer size and energy. Taking both forwarding and receiving capabilities into account, we finally present a forwarding set mechanism, which could be deduced to a multiple knapsack problem to maximize the forwarding profit. Consequently, we take all the above studies into the design of a context-aware message forwarding algorithm (CAMF). Extensive trace-driven simulations show that CAMF outperforms other existing algorithms greatly. In fact, it achieves a surprisingly high routing performance while consumes low transmission cost and resource in MSN.

Optimal Forwarding in Opportunistic Delay Tolerant Networks With Meeting Rate Estimations

Data transfer in opportunistic delay tolerant networks (DTNs) must rely on unscheduled sporadic meetings between nodes. The main challenge in these networks is to develop a mechanism based on which nodes can learn to make nearly optimal forwarding decision rules despite having no a priori knowledge of the network topology. The forwarding mechanism should ideally result in a high-delivery probability, low-average latency, and efficient usage of the network resources. In this paper, we propose both centralized and decentralized single-copy message forwarding algorithms that, under relatively strong assumptions about the networks behavior, minimize the expected latencies from any node in the network to a particular destination. After proving the optimality of our proposed algorithms, we develop a decentralized algorithm that involves a recursive maximum-likelihood procedure to estimate the meeting rates. We confirm the improvement that our proposed algorithms make in the system performance through numerical simulations on datasets from synthetic and real-world opportunistic networks.

Message Forwarding in Sparsely Connected Wireless Networks Using Rateless Codes

Rateless codes can reduce retransmission costs over erasure channels. Existing routing algorithms using rateless codes assume densely connected networks and predecide the forwarder nodes, which subsequently participate in message forwarding. Using a rateless code, which is easy to analyze and implement, we propose practically implementable opportunistic message forwarding algorithms for sparsely connected networks, in which all the nodes can potentially participate in forwarding, and study their performance through simulations.

Identifying Influential Nodes for Efficient Routing in Opportunistic Networks

—Opportunistic networks exploit human mobility and consequent device-to-device contacts to opportunistically create data paths over time. Identifying influential nodes as relay is a crucial problem for efficient routing in opportunistic networks. The degree centrality method is very simple but of little relevance. Although closeness centrality and betweenness centrality can effectively identify influential nodes, they are incapable to be applied in large-scale networks due to the high computational complexity. In this paper, we focus on designing an effective centrality ranking metric with low computational complexity in opportunistic networks. We propose the semi locally evaluated centrality metric to identify influential nodes for message forwarding in opportunistic networks. We also present a simple message forwarding algorithm, and employ real world mobility traces and synthetic mobility traces to evaluate the benefits of the proposed semi locally evaluated centrality metric. Results demonstrate the efficiency of the proposed metric in opportunistic networks.

A self-similar super-peer overlay construction scheme for super large-scale P2P applications

Unstructured peer-to-peer (P2P) overlay networks with two-layer hierarchy, comprising an upper layer of super-peers and an underlying layer of ordinary peers, are used to improve the performance of large-scale P2P applications like content distribution and storage. In order to deal with continuous growth of participating peers, a scalable and efficient super-peer overlay topology is essential. However, there is relatively little research conducted on constructing such super-peer overlay topology. In the existed solutions, the number of connections required to be maintained by a super-peer is in direct proportion to the total number of super-peers. For super large-scale P2P applications, i.e. the number of participating peer is over 1,000,000, these solutions are not scalable and impractical. Therefore, in this paper, we propose a scalable hierarchical unstructured P2P system in which a self-similar square network graph (SSNG) is proposed to construct and maintain the super-peer overlay topology adaptively. The SSNG topology is a constant-degree topology in which each node maintains a constant number of neighbor nodes. Moreover, a simple and efficient message forwarding algorithm is presented to ensure each super-peer to receive just one flooding message. The analytical results showed that the proposed SSNG-based overlay is more scalable and efficient than the perfect difference graph (PDG)-based overlay proposed in the literature.

MDPF: Minimum Distance Packet Forwarding for Search Applications in Mobile Ad Hoc Networks

This paper introduces a message forwarding algorithm for search applications within mobile ad hoc networks that is based on the concept of selecting the nearest node from a set of designated nodes. The algorithm, which is called Minimum Distance Packet Forwarding (MDPF), uses routing information to select the node with the minimum distance. The goal of the proposed algorithm is to minimize the average number of hops taken to reach the node that holds the desired data. Numerical analysis and experimental evaluations using the network simulation software ns2 were performed to derive the lower and upper bounds of the confidence interval for the mean hop count between the source node of the data request, on one hand, and the node that holds the desired data and the last node in the set of search nodes, on the other hand. In the experimental evaluation, the performance of MDPF was compared to that of Random Packet Forwarding (RPF) and Minimal Spanning Tree Forwarding (MSTF). The results agreed with the numerical analysis results and demonstrated that MDPF offers significant hop count savings and smaller delays when compared to RPF and MSTF.