Control Packets Research Articles

OpenPATH: Application aware high-performance software-defined switching framework

Currently, core networking architecture is facing disruptive developments, due to the emergence of SDN for control, NFV for services and so on. SDN promises more versatility in routing and managing traffic flows, while NFV represents a large shift in how network functions and services are built, deployed, and managed. We present OpenPATH (aPplication Aware software-defined swiTcHing framework)—A software-defined switching framework for NFV processing and orchestration of Network Functions (NFs) and steering the flows through service chains. Inspired by the potential benefits of encapsulating the application logic into the SDN dataplane, OpenPATH is built on the concept of a modular dataplane, which consists of two layers - switching fabric layer to control packet forwarding; and switch management layer, which inspects the incoming packets, steers the flows through a sequence of NFs and determines the next forward/drop action. The application logic of the NFs can be introduced and pushed to the dataplane at runtime and the framework offers fast packet processing and I/O functionalities to support NF parallelism in the Service Function Chaining (SFC) scenarios. OpenPATH is a modular framework for software switches and offers flexibility for programming run time functions depending on the dynamic behavior of the network traffic and cyberattacks. The architecture components are not hard-coded or rigidly implementations in conventional switches/bridges and standard OpenFlow based SDN stacks. The design allows the vendors, operators, or developers to configure policies at run time and deploy custom logic and NF (also series of NFs) through software programs embedded in the switching fabric. While the basic concept is similar to some pioneering works in this area, OpenPATH does not sacrifice portability, performance, or security for programmability. The OpenPATH as a programmable switching platform takes a different approach to meet most of the requirements of application-aware and intent-based networking. OpenPATH helps administrators to quickly configure network security services using a rich set of standard APIs, with simplified flow tables. The evaluation shows that our design can leverage complex states in the data plane without overloading the SDN controller. Compared to conventional SDN methods, this provides much greater versatility and precision. The key findings indicate that OpenPATH achieves lower cost for scaling, higher overall throughput, and reductions in latency for real-world service chains.

A novel clustering method for fault recovery and routing in mobile ad‐hoc networks

SummaryMobile ad‐hoc network (MANET) is a group of self‐organized autonomous wireless devices that serve communication in human unattended and emergency environments. The network is decentralized and uses wireless links for communication, which is vulnerable to network resource depletion rapidly. Energy and link stability are vital factors that support the prolonged operation of the network, obstructing earlier resource depletions. These depletions are overwhelmed with the help of scattered, isolated nodes; the process of augmenting them increases the control overhead. We propose a genetic algorithm‐based routing (GAR) with fault route recovery (FRR) caused due to isolated nodes. In this method, clustering is used for energy balancing for retaining the live nodes' count reliably. The FRR phase prevents cluster head flooding using the local rerouting process. The former phase of GAR‐FFR governs the network's energy optimization aiming at controlled energy consumption. The later part reduces routing overhead due to route failures, preventing backtracking to the cluster head. The proposed GAR‐FFR is analyzed using the following metrics: throughput, packet delivery ratio, live nodes count, remaining energy, and routing overhead. The proposed GAR‐FRR achieves 15.4% high throughput, 16.29% high live nodes, 8.9% high remaining energy, and 21.04% fewer control packets for different rounds, compared with the existing A‐ECOPS and REAC‐IN methods.

Multicast DIS attack mitigation in RPL-based IoT-LLNs

The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) was standardised by the IETF ROLL Working Group to address the routing issues in the Internet of Things (IoT) Low-Power and Lossy Networks (LLNs). RPL builds and maintains a Destination Oriented Directed Acyclic Graph (DODAG) topology using pieces of information propagated within the DODAG Information Object (DIO) control message. When a node intends to join the DODAG, it either waits for DIO or sends a DODAG Information Solicitation (DIS) control message Multicast to solicit DIOs from nearby nodes. Nevertheless, sending Multicast DIS messages resets the timer that regulates the transmission rate of DIOs to its minimum value, which leads to the network’s congestion with control messages. Because of the resource-constrained nature of RPL-LLNs, the lack of tamper resistance, and the security gaps of RPL, malicious nodes can exploit the Multicast DIS solicitation mechanism to trigger an RPL-specification-based attack, named DIS attack. The DIS attack can have severe consequences on RPL networks, especially on control packets overhead and power consumption. In this paper, we use the Cooja–Contiki simulator to assess the DIS attack’s effects on both static and dynamic PRL networks. Besides, we propose and implement a novel approach, namely RPL-MRC, to improve the RPL’s resilience against DIS Multicast. RPL-MRC aims to reduce the response to DIS Multicast messages. Simulation results demonstrate how the attack could damage the network performance by significantly increasing the control packets overhead and power consumption. On the other hand, the RPL-MRC proposed mechanism shows a significant enhancement in reducing the control overhead and power consumption for different scenarios.

Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks

Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased.

S-CDCA: a semi-cluster directive-congestion protocol for priority-based data in WSNs

The internet of things (IoT) protocols and regulations are being developed forvarious applications includes: habitat monitoring, machinery control, general health-care, smart-homes and more. A great part of I0T comprised of sensors nodes in connected networks (i.e. sensor networks.). A sensor network is a group of nodes with sensory module and computational elements connected through network interfaces. The most interesting type of sensor networks are wireless sensor networks. The nodes here are connected through wirless interfaces. The shared medium between these nodes, creates different challenges. Congestion in such network is ineavitable. Different models andmethods were proposed to alleviate congestion in wireless sensor networks.This paper presents a semi-cluster directive congestion method that allivatenetwork congestion forpriority-baseddata transmission. The method simprove the network performance by implementing temporary cluster forlow level priority data packets while providing a clear link between highpriority data source node and the network base station. Simulation resultsshow that. The proposed method outperformes ad hocOn-demand distance vector (AODV) reactive procotol approach and priority-based congestion control dynamic clustering (PCCDC) a cluster-based methodin network energy consumption and control packets overhead during network operation.The proposed method also shows comparative improvments in end-to-enddelays versus PCCDC.

Collision Avoidance Geographic P2P-RPL in Multi-Hop Indoor Wireless Networks

In home and building automation applications, wireless sensor devices need to be connected via unreliable wireless links within a few hundred milliseconds. Routing protocols in Low-power and Lossy Networks (LLNs) need to support reliable data transmission with an energy-efficient manner and short routing convergence time. IETF standardized the Point-to-Point RPL (P2P-RPL) routing protocol, in which P2P-RPL propagates the route discovery messages over the whole network. This leads to significant routing control packet overhead and a large amount of energy consumption. P2P-RPL uses the trickle algorithm to control the transmission rate of routing control packets. The non-deterministic message suppression nature of the trickle algorithm may generate a sub-optimal routing path. The listen-only period of the trickle algorithm may lead to a long network convergence time. In this paper, we propose Collision Avoidance Geographic P2P-RPL, which achieves energy-efficient P2P data delivery with a fast routing request procedure. The proposed algorithm uses the location information to limit the network search space for the desired route discovery to a smaller location-constrained forwarding zone. The Collision Avoidance Geographic P2P-RPL also dynamically selects the listen-only period of the trickle timer algorithm based on the transmission priority related to geographic position information. The location information of each node is obtained from the Impulse-Response Ultra-WideBand (IR-UWB)-based cooperative multi-hop self localization algorithm. We implement Collision Avoidance Geographic P2P-RPL on Contiki OS, an open-source operating system for LLNs and the Internet of Things. The performance results show that the Collision Avoidance Geographic P2P-RPL reduced the routing control packet overheads, energy consumption, and network convergence time significantly. The cooperative multi-hop self localization algorithm improved the practical implementation characteristics of the P2P-RPL protocol in real world environments. The collision avoidance algorithm using the dynamic trickle timer increased the operation efficiency of the P2P-RPL under various wireless channel conditions with a location-constrained routing space.

A Reinforcement Learning Routing Protocol for UAV Aided Public Safety Networks.

In Public Safety Networks (PSNs), the conservation of on-scene device energy is critical to ensure long term connectivity to first responders. Due to the limited transmit power, this connectivity can be ensured by enabling continuous cooperation among on-scene devices through multipath routing. In this paper, we present a Reinforcement Learning (RL) and Unmanned Aerial Vehicle- (UAV) aided multipath routing scheme for PSNs. The aim is to increase network lifetime by improving the Energy Efficiency (EE) of the PSN. First, network configurations are generated by using different clustering schemes. The RL is then applied to configure the routing topology that considers both the immediate energy cost and the total distance cost of the transmission path. The performance of these schemes are analyzed in terms of throughput, energy consumption, number of dead nodes, delay, packet delivery ratio, number of cluster head changes, number of control packets, and EE. The results showed an improvement of approximately in EE of the clustering scheme when compared with non-clustering schemes. Furthermore, the impact of UAV trajectory and the number of UAVs are jointly analyzed by considering various trajectory scenarios around the disaster area. The EE can be further improved by using Two UAVs on Opposite Axis of the building and moving in the Opposite directions (TUOAO) when compared to a single UAV scheme. The result showed that although the number of control packets in both the single and two UAV scenarios are comparable, the total number of CH changes are significantly different.

MEDIUM ACCESS CONTROL BASED BUSY TONE ROUTING IN MANET

Several MANET designs looked into renewable resource efficient protocols. The amount of energy dissipated by MANET nodes is an important coordinating component. In monitoring applications, power usage is ensured, and battery depletions are reduced to avoid frequent replacement. MANET's primary goal is to relay data by utilising energy-efficient routing techniques and extending the network's lifespan. In this research, we provide an Energy Efficient Protocol on Remaining Energy, a new paradigm for MANET multicasting. Our idea is based on a tone system that integrates solutions across the Medium Access Control (MAC) layer to deliver more efficiency and better performance. To provide increased stability and lower energy consumption, the protocol includes a new construction mechanism for mobile nodes that uses a clustering strategy based on distance and remaining energy. We also propose modifying the conventional multicast flow by introducing unicast links between clusters. In addition, we describe a strategy based on a busy tone system to eliminate excessive control overhead produced by control packets in error recovery in our model. The simulation results are displayed in NS2, and they indicate improvements in reliability, packet delivery ratio, energy usage, and throughput.

Remote observer-based robust control for cyber-physical systems under asynchronous DoS attacks: an intelligent approach

In this paper, the input-to-state stability (ISS) control problem is studied for cyber-physical systems (CPSs) in the presence of asynchronous denial-of-service (DoS) attacks. To enhance the exponential ISS, an intelligent packet-based control method with buffering is proposed by introducing the acknowledgement signal (ACK), in which the trial transmission attempts of the control packet are intelligently determined by the situation (successful or failed) of its last sampling transmission instant after identifying the unnecessary transmission points and the necessary transmission points. Then, inspired by the packet-based control technology with buffering, the sufficient condition for attempting transmission of the control packet is given, in which the exponential ISS with maximum robustness index can be preserved. Compared with the existing method with a fixed transmission rate for the control packet, it is shown that the considered framework improves the exponential ISS performance with equal or less communication resource costs.

Reduction of energy consumption and delay of control packets in Software-Defined Networking

The energy consumption of network devices is a significant part of the network's energy costs. Recently, Software-Defined Networking (SDN) has been suggested as a suitable and stable solution to decrease energy consumption. The main concern is how to manage resources for optimum energy consumption in SDN. Hence, this paper proposes a binary linear programming model. This model manages (on or off devices) switches, controllers, and SDN links based on the number of flows at the network edge, the processing capability of the controllers, the distance between switches and controllers, and the traffic. Therefore, with this model, the lowest energy consumption, and the lowest delay of control packets is achieved. The results show that this model, on average, has saved 40% of energy consumption, and it has also had up to 80% decrement when there is less network traffic. In addition, this model has decreased 68% of the delay of controlling packets with 70% decrement in less traffic.

Adaptive Control Packet Broadcasting Scheme for Faster 6TiSCH Network Bootstrapping

The IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH) Working Group released 6TiSCH minimal configuration (6TiSCH-MC) standard for 6TiSCH network bootstrapping. 6TiSCH-MC allocates only one shared cell per slotframe, known as a minimal cell, to transmit all types of control packets. Our Markov Chain-based probabilistic analysis reveals that few network parameters have a high impact on the performance of 6TiSCH network formation due to increasing congestion in the minimal cell with the increased number of nodes. This work aims to improve the 6TiSCH network formation process by reducing congestion in the minimal cell. For this, the Trickle algorithm, which is used for controlling the rate of routing information-carrying packet transmission is modified so that sufficient routing information can be provided without congesting the minimal cell. To reduce the congestion further, a slotframe window (SW)-based adaptive scheme is proposed by which nodes are restricted to transmit their control packets frequently. The proposed dynamic Trickle algorithm and SW-based scheme are implemented on Contiki-NG and evaluated using FIT IoT-LAB testbed. The experimental results show that both the proposed schemes together improve the joining time and energy consumption of the pledges compared to the state-of-the-art schemes. Additionally, both the proposed schemes provide fair control packet transmission opportunities among the nodes in a network.

Enabling Reliable UAV Control by Utilizing Multiple Protocols and Paths for Transmitting Duplicated Control Packets.

In the last ten years, supported by the advances in technologies for unmanned aerial vehicles (UAVs), UAVs have developed rapidly and are utilized for a wide range of applications. To operate UAVs safely, by exchanging control packets continuously, operators should be able to monitor UAVs in real-time and deal with any problems immediately. However, due to any networking problems or unstable wireless communications, control packets can be lost or transmissions can be delayed, which causes the unstable drone control. To overcome this limitation, in this paper, we propose MuTran for enabling reliable UAV control. MuTran considers the packet type and duplicates only control packets, not data packets. After that, MuTran transmits the original and duplicate packets through multiple protocols and paths to improve the reliability of control packet transmissions. We designed MuTran and conducted a lot of theoretical analyses to demonstrate the validity of MuTran and analyze it from various aspects. We implemented MuTran on real devices and evaluated MuTran using the devices. We conducted experiments to verify the limitations of the existing systems and demonstrate that control packets can be transmitted more stably by using MuTran. Through the analysis and experimental results, we confirmed that MuTran reduces the control packet transfer delay, which improves the reliability and stability of controlling UAVs.

Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study.

Owing to automation trends, research on wireless sensor networks (WSNs) has become prevalent. In addition to static sinks, ground and aerial mobile sinks have become popular for data gathering because of the implementation of WSNs in hard-to-reach or infrastructure-less areas. Consequently, several data-gathering mechanisms in WSNs have been investigated, and the sink type plays a major role in energy consumption and other quality of service parameters, such as packet delivery ratio, delay, and throughput. However, the data-gathering schemes based on different sink types in WSNs have not been investigated previously. This paper reviews such data-gathering frameworks based on three different types of sinks (i.e., static, ground mobile, and aerial mobile sinks), analyzing the data-gathering frameworks both qualitatively and quantitatively. First, we examine the frameworks by discussing their working principles, advantages, and limitations, followed by a qualitative comparative study based on their main ideas, optimization criteria, and performance evaluation parameters. Next, we present a simulation-based quantitative comparison of three representative data-gathering schemes, one from each category. Simulation results are shown in terms of energy efficiency, number of dead nodes, number of exchanged control packets, and packet drop ratio. Finally, lessons learned from the investigation and recommendations made are summarized.

An MPTCP-Based Transmission Scheme for Improving the Control Stability of Unmanned Aerial Vehicles.

Recently, unmanned aerial vehicles (UAVs) have been applied to various applications. In order to perform repetitive and accurate tasks with a UAV, it is more efficient for the operator to perform the tasks through an integrated management program rather than controlling the UAVs one by one through a controller. In this environment, control packets must be reliably delivered to the UAV to perform missions stably. However, wireless communication is at risk of packet loss or packet delay. Typical network communications can respond to situations in which packets are lost by retransmitting lost packets. However, in the case of UAV control, delay due to retransmission is fatal, so control packet loss and delay should not occur. As UAVs move quickly, there is a high risk of accidents if control packets are lost or delayed. In order to stably control a UAV by transmitting control messages, we propose a control packet transmission scheme, ConClone. ConClone replicates control packets and then transmits them over multiple network connections to increase the probability of successful control packet transmission. We implemented ConClone using real equipment, and we verified its performance through experiments and theoretical analysis.

An energy-efficient routing protocol for the Internet of Things networks based on geographical location and link quality

In the design of Internet of Things (IoT), sensor nodes are used in collecting data from an environment and sending it to a base station or sink for future processing. These sensor nodes have some resource constraints such as power supply. Hence, in order to prolong the network lifetime, we need to manage the energy consumption of these sensor devices. Thus, in this paper, a tree-based routing protocol is proposed that is efficient in power consumption and reduces the end-to-end delay in energy-efficient green-IoT networks with a mobile sink. Two new different mechanisms are introduced in the proposed protocol for managing the routing in the network. The first mechanism is an improved version of the geographic routing algorithm, which is more reliable and energy-balanced. The second mechanism is a tree-based structure that can be created with the minimum control packets and updated with an efficient procedure. Simulation results indicate that the proposed routing algorithm is superior to the existing ones in terms of energy consumption, network lifetime, delay, and throughput.

Soft Computing approach to enhance the Performance of AODV (Ad-hoc On-Demand Distance Vector) Routing Protocol using Active Route TimeOut (ART) Parameter in MANETs

While its advancement inside MANETs, the AODV routing protocol convention has been and stays a powerful and gainful examination protocol, with association with its course Active Route Timeout (ART), AODV utilizes a predictable worth that demonstrates the time and the course which may stay dynamic in the directing table. A long period of the course might be chosen powerfully, dependably through the estimation, as opposed to reliable worth. For this reason, a Fuzzy rationale framework is utilized to procure the versatile qualities for ART dependent on the transmitter conditions and interceding hubs.As indicated by the pre-essentials of the International Engineering Task Force (IETF), we shouldn't be taking stil qualities in the powerful atmosphere. Subsequently, ART's tweaking of turncoat esteems is accomplished by applies fluffy principles on the info factors hop-count, Sent Control Packet, and Nodes Number. AODV convention yield is assessed after the utilization of Fuzzy based methodology. The proficiency of AODV and FBARTAODV Routing Protocols for Mobile Ad Hoc Networks will be examined with results. In this paper we give outcome show so as to the FBARTAODV perform enhanced compared to the in progress AODV.

FTTCNF- Novel Approach for Fault Tolerant Topology Control in Manet

In wireless networks it is observed that as nodes move unpredictably sudden link disconnections occur during transmission. This leads to frequent path changes and multiple path discoveries which subsequently increase transmission of control packets in network. The nodes in the network simply rebroadcast the received route request (RREQ) packet if they do not have the route to the required destination. In addition to this, frequent hello messages for neighbour set construction and maintenance also increase control message count in the network causing a flooding issue. In order to mitigate these problems, the proposed Fault Tolerant Topology Control Neuro Fuzzy method (FTTCNF), incorporates measures to improve the network stability and to reduce the control packets in the network. These measure 1.reduce control message transmissions among neighbours by finding a stable path 2. neighbour node distance is computed based on the reception of a signal strength Indication (RSSI), 3. path stability is decided by the link expiry time (LET) which can be used to predict the neighbour mobility deviations. These factors, ( above mentioned distance, path stability factor PSF, and LET) are subjected to the fuzzification process to identify the fuzzy rule values and are given as input to the neuron formation stage. Final neuron value is computed for all available paths and the maximum value path is chosen for data transmission. Energy level monitoring is also applied at each node to check the node’s current energy and should it go below the energy threshold level the node by itself, joining the routing process is avoided. Simulation results have proved that the proposed method significantly reduces the routing overhead and improves the stability of path during data transmission.

Repeated game theory-based reducer selection strategy for energy management in SDWSN

The sensor-generated data by Internet of Things are considered to be the most common source of big data. A wide range of applications are relying on these data for analytics. While a considerable amount of data is sufficient for the application users to get valuable insights, sending vast amount of data to the cloud seems inappropriate and it only increases the communication cost in the network. It is well-known that an increase in communication cost increases energy depletion in the network. Since sensor nodes have a restricted power supply, it is necessary to harness the energy of nodes to prolong the network lifetime. In this paper, a solution for energy management of sensor nodes is proposed by integrating the software defined framework with the sensor network, software defined wireless sensor networks (SDWSN), that aids in processing the data inside the network before transferring it to the sink node. To this context, a game model has been formulated for selecting the appropriate nodes as reducers which will execute the reducer function. The software defined network (SDN) controller, geographically placed outside of the wireless sensor network, is responsible for selecting the reducers and dynamically load reducing function on them. Based on the selection, a routing protocol, routing via respective reducer (RVRR), that forwards data packets via in-network processing path and control packets via common path has been proposed. This remarkably reduces the communication cost, thereby prolonging the lifetime of the deployed network. The RVRR algorithm is implemented in NS-3 simulator to evaluate the performance of proposed work in SDWSN environment.

DEDA: An algorithm for early detection of topology attacks in the internet of things

The internet of things (IoT) is used in domestic, industrial as well as mission-critical systems including homes, transports, power plants, industrial manufacturing and health-care applications. Security of data generated by such systems and IoT systems itself is very critical in such applications. Early detection of any attack targeting IoT system is necessary to minimize the damage. This paper reviews security attack detection methods for IoT Infrastructure presented in the state-of-the-art. One of the major entry points for attacks in IoT system is topology exploitation. This paper proposes a distributed algorithm for early detection of such attacks with the help of predictive descriptor tables. This paper also presents feature selection from topology control packet fields. The performance of the proposed algorithm is evaluated using an extensive simulation carried out in OMNeT++. Performance parameter includes accuracy and time required for detection. Simulation results presented in this paper show that the proposed algorithm is effective in detecting attacks ahead in time.

Sustainable cloud computing for cognitive intent based networks

Intent based networks enable auto-configuration and require low latency access to cloud platforms. The use of cloud platforms incurs high operational costs. Low latency access can be realized by siting data centres close to subscribers. This paper proposes aquaria data centers with low operating costs and latency. In LTE, cloud platforms are normally accessed via the packet network gateway reachable via the serving gateway and mobility management entity. Aquaria data centers are sited close to LTE subscribers and accessed via the mobility management entity. This reduces the size of control packets in the LTE network. Simulations show that the proposed architecture reduces the size of control packets by up to 49.7% and 99.3% when header packets are uncompressed and compressed respectively. The delay associated with receiving configuration information is reduced by 50% on average. The channelcapacity is enhanced by up to 22.8% on average.
 Keywords: Data centers, LTE-Advanced, Peak Age of Information, Channel Capacity, Header (Control) Packet