Packet Aggregation Research Articles

An IoT-based packet aggregation mechanism for the SDN-based wide area networks

The Internet of Things (IoT) is destined to play a crucial role in our daily lives. Numerous short packets are sent over the networks due to these IoT devices' communication with one another or with the relevant servers via the Internet, which causes an increase in the bps and pps in the network nodes, high overheads, and inefficient performance of the networks. Many packet aggregation mechanisms have been developed and studied to solve these issues. Among them, some works are about the aggregation of the IoT packets in the WAN area; however, they have few studies and discussions about selecting the aggregator nodes and the possible options. In this work, a packet aggregation mechanism is proposed for near-the-edge SDN-based AS networks in the WAN area, which can select the aggregation type and the aggregator nodes among the possible options. The simulation results of the proposed mechanism are presented for different options, and the related discussions and comparisons are made. The results show improvements in the network efficiency for different modes of the proposed packet aggregation mechanism related to the non-aggregation mode and simple/app-level aggregation in all network nodes.

A dynamic channel aggregation strategy with a maximum aggregation number in cognitive radio networks based on channel classification

In traditional cognitive radio networks (CRNs), users are generally divided into two categories: primary users (PUs) and secondary users (SUs). The transmission rates of different channels may vary due to the complexities of network transmissions. Therefore, in this paper, a channel classification mechanism that divides the channels in the system into high-speed channels and low-speed channels according to their transmission capacity is proposed. In addition, to improve the performance of users, a dynamic channel aggregation strategy for CRNs with two types of channels is proposed. In this strategy, packets first consider accessing high-speed channels. We set a fixed channel aggregation strategy for PU packets and a dynamic channel aggregation strategy for SU packets. The number of channel aggregation of SU packets is restricted by the maximum aggregation number. Based on the proposed strategy, a multi-service discrete-time queueing model is established and analyzed, and the performance index expressions of PU packets and SU packets are derived. Moreover, we conduct numerical experiments, obtain the system performance figures and analyze the system performance. Finally, the performance of the proposed channel aggregation strategy is compared with that of the non-aggregation strategy, verifying the effectiveness of the proposed channel aggregation strategy.

Data Aggregation through Hybrid Optimal Probability in Wireless Sensor Networks


 INTRODUCTION: In the realm of Wireless Sensor Networks (WSN), effective data dissemination is vital for applications like traffic alerts, necessitating innovative solutions to tackle challenges such as broadcast storms.
 OBJECTIVES: This paper proposes a pioneering framework that leverages probabilistic data aggregation to optimize communication efficiency and minimize redundancy.
 METHODS: The proposed adaptable system extracts valuable insights from the knowledge base, enabling dynamic route adjustments based on application-specific criteria. Through simulations addressing bandwidth limitations and local broadcast issues, we establish a robust WSN-based traffic information system.
 RESULTS: By employing primal-dual decomposition, the proposed approach identifies optimal packet aggregation probabilities and durations, resulting in reduced energy consumption while meeting latency requirements.
 CONCLUSION: The efficacy of proposed method is demonstrated across various traffic and topology scenarios, affirming that probabilistic data aggregation effectively mitigates the local broadcast problem, ultimately leading to decreased bandwidth demands.

Value Gain-based Power Line Subcarrier Aggregation Method under Colored Noise

With the large-scale power electronic equipment connected to the distribution network in the form of a new power system, the colored noise generated by power equipment will greatly reduce the efficiency of data transmission. The power line communication subcarrier grouping aggregation method features high transmission efficiency, excellent reliability, and high stability, which can improve the anti-interference and anti-noise performance of power line subcarriers. However, traditional subcarrier packet aggregation methods neglect the network topology changes and node service requirements, resulting in low adaptability of available subcarriers for power electronics scenarios. Therefore, we propose a value gain-based power line subcarrier aggregation method under colored noise. It can achieve adaptive colored noise awareness and dynamically optimize the subcarrier grouping aggregation. Simulation results demonstrate the excellent performance of the proposed algorithm in terms of availability and utilization efficiency.

Drone’s node placement algorithm with routing protocols to enhance surveillance

<span lang="EN-US">Flying ad-hoc network (FANET) is characterized by key component features such as communication scheme, energy awareness, and task distribution. In this research, a surveillance space considering standard petroleum pipe was created with three drones viz: drone 1 (D1), master drone (DM), and drone 2 (D2) to survey as FANET. DM aggregate packets from D1, D2 and communicate with the static ground control station (SGCS). The starting point of the three drones and their trajectories during deployment were calculated and simulated. Selection of DM, D1, and D2 was done using battery level before take-off. Simulation results show take-off time difference which depends on the distance of each drone to the SGCS during deployment. D1 take-off first, while DM and D2 followed after 0.0704 and 0.1314 ms respectively. The position-oriented routing protocols results indicated variation of information flow within time notch due to variation in the density of the transmitted packets. Packets delivery periods are 0.00136×10<sup>3</sup> sec, 0.00110×10<sup>3</sup> sec, and 0.00246×10<sup>3</sup> sec for time notch 1, 2, and aggregating time notch respectively. From the results obtained, two algorithms were used successfully in deploying the drones</span>

Energy-aware message distribution algorithm for enhance FANET pipeline surveillance reliability

Features such as the communication scheme, energy awareness, and task distribution amongst others are the key component that characterizes the Flying Ad-hoc Network (FANET). The operational efficiency in FANET surveying a specific region is affected by the nature of the UAVs' node placement, routing protocol, energy-aware task distribution, and node interaction amongst others. In this paper, Drone 1 (D1), Master Drone (DM), and Drone 2 (D2) were used to survey a pipeline of length 12.2 m. This paper aims at minimising energy use by drones during surveillance using energy-aware node exchange technique, task interaction and distribution scheme for each UAV. Due to fast energy depletion of DM due to packets aggregation, its election is based on the UAV with the highest energy before take-off. For two different simulations, 14,697.0 J and 14,836.6 J were obtained for DM. To avoid system failure due to fast energy loss of DM, the drones swapped positions and status. First swapping command comes up when DM loses 50% of its energy, while the second command occurs when it further loses 15%. Return to base threshold energy is computed for the three UAVs to avoid crash due to insufficient energy during surveillance. DM returns to base threshold energy for both single and double swapping simulation were 658.105 J and 652.456 J respectively. From the results obtained the algorithms were able to exchange nodes to maximize energy usage and perform an interaction-based task distribution for cooperative task sharing during surveillance. This translates into longer surveillance time and effective telemetry data aggregation.

A Deep Learning-Based Encrypted VPN Traffic Classification Method Using Packet Block Image

Network traffic classification has great significance for network security, network management and other fields. However, in recent years, the use of VPN and TLS encryption had presented network traffic classification with new challenges. Due to the great performances of deep learning in image recognition, many solutions have focused on the deep learning-based method and achieved positive results. A traffic classification method based on deep learning is provided in this paper, where the concept of Packet Block is proposed, which is the aggregation of continuous packets in the same direction. The features of Packet Block are extracted from network traffic, and then transformed into images. Finally, convolutional neural networks are used to identify the application type of network traffic. The experiment is conducted using captured OpenVPN dataset and public ISCX-Tor dataset. The results shows that the accuracy is 97.20% in OpenVPN dataset and 93.31% in ISCX-Tor dataset, which is higher than the state-of-the-art methods. This suggests that our approach has the ability to meet the challenges of VPN and TLS encryption.

Performance Analyses of Uplink MU-OFDMA Hybrid Access MAC in IEEE 802.11ax WLANs

Future wireless local area networks (WLANs) are expected to have numerous stations (STAs) with diverse Quality of Service requirements. IEEE 802.11ax is the current WLAN standard proposed to meet these requirements. This article analyzes the uplink-multiuser-orthogonal frequency division multiple access-hybrid access (HA) mechanism of the 802.11ax system under error-prone channel conditions. We propose an enhanced Markov chain model for analyzing such a WLAN system. By solving the system model, we derive vital systems performance metrics, such as aggregate and per-STA throughput, random access (RA) capability packet loss probability, mean delay, jitter, fairness, and worst-case delay bounds. Our analysis also considers different physical (PHY) and medium access control (MAC) layer aspects, such as channel bandwidth, the number of resource units (RUs), packet aggregation feature, fading, path-loss, modulation and coding schemes (MCS), etc. Furthermore, we have studied the MCS link adaptation-based dynamic HA process where the RUs are dynamically adapted between scheduled access and RA mechanisms. Additionally, to capture the role of PHY and MAC layer parameters on multi-Basic service set scenarios, we have integrated the Markov chain-based modeling with the stochastic geometry-based model. Our analytical model has been validated against extensive simulations, and the tradeoff between the metrics is studied.

Comparative study for evaluating the cost efficiency of 5G Ethernet mobile fronthaul networks

With the advances in mobile network technologies, the fronthaul is being evolved to centralized and cloud networks, leading to the emergence of various optical multiplexing architectures. Among others, the Ethernet-based packet switching network is considered one of the most promising concepts due to the inherent merits of Ethernet such as backward compatibility, high reliability, and cost reduction. This work aims at evaluating the Ethernet-based mobile fronthaul network by comparing it with other configuration options. In particular, we calculate and compare the total cost of ownership (TCO) in order to emphasize the cost efficiency of the 5G Ethernet fronthaul network. For this, we analyze the packet aggregation capabilities of the Ethernet fronthaul through queueing latency modeling. Hence, we show that the statistical multiplexing enabled by packet switching reduces the cost related to optical transceiver modules and subsequently fiber optic cabling, which eventually allows for the TCO to be less than 70% of the active transparent system.

Novel Method of Reducing the Allocated Bandwidth by Voip

Abstract Old telecommunication systems are gradually being replaced by a new system that works over IP networks, which is known as voice over internet protocol (VoIP). VoIP has several merits (e.g., very cheap call rate), which make it increasingly popular in the telecommunication world. However, VoIP faces numerous impediments that decelerate its promotion. One of the top impediments is the wasted bandwidth caused by VoIP systems. Numerous methods have been proposed to handle this impediment, including packet aggregation methods. This paper proposes a novel aggregation method, called packet aggregation and carrier header (PA-CH), to reduce the amount of the large bandwidth caused by VoIP. As the name suggests, PA-CH saves in bandwidth by aggregating the packets in a header and using the redundant fields in the packet header to carry a portion of the packet voice data. The performance of the introduced PA-CH method was investigated based on three main metrics, namely, link capacity, allocated bandwidth reduction, and voice data shortening. Simulation results indicate that the proposed PA-CH method outperforms the comparison methods in three factors. For instance, the proposed method’s allocated bandwidth reduction ratio reaches 51% when the number of calls running concurrently reaches 100. Therefore, the proposed PA-CH method achieves its goal of reducing the wasted bandwidth caused by VoIP.

FAM: A frame aggregation based method to infer the load level in IEEE 802.11 networks

In many environments, connected devices are exposed to and must choose between multiple Wi-Fi networks. However, the procedure for selecting an access point is still based on simple criteria that consider the device to be unique in the network. In particular, the network load is not taken into account even though it is a key parameter for the quality of service and experience.In this paper, we investigate how an unmodified vanilla device could estimate the load of a network in the user space with no interventions from the access points. In this regard, we propose a novel and practical method, FAM (Frame Aggregation based Method). It leverages the frame aggregation mechanism introduced in recent IEEE 802.11 amendments to estimate the network load through its channel busy time fraction. FAM combines an active probing technique to measure the actual packet aggregation and Markovian models that provide the expected rate as a function of the volume and nature of the traffic on the network. We validate the effectiveness of FAM against both ns-3 simulations and test-bed experiments under several scenarios. Results show that our method FAM is able to infer the network load with a granularity based on six different levels of network loads for the considered scenarios.

Performance Analysis of Packet Aggregation Mechanisms and Their Applications in Access (e.g., IoT, 4G/5G), Core, and Data Centre Networks.

The transmission of massive amounts of small packets generated by access networks through high-speed Internet core networks to other access networks or cloud computing data centres has introduced several challenges such as poor throughput, underutilisation of network resources, and higher energy consumption. Therefore, it is essential to develop strategies to deal with these challenges. One of them is to aggregate smaller packets into a larger payload packet, and these groups of aggregated packets will share the same header, hence increasing throughput, improved resource utilisation, and reduction in energy consumption. This paper presents a review of packet aggregation applications in access networks (e.g., IoT and 4G/5G mobile networks), optical core networks, and cloud computing data centre networks. Then we propose new analytical models based on diffusion approximation for the evaluation of the performance of packet aggregation mechanisms. We demonstrate the use of measured traffic from real networks to evaluate the performance of packet aggregation mechanisms analytically. The use of diffusion approximation allows us to consider time-dependent queueing models with general interarrival and service time distributions. Therefore these models are more general than others presented till now.

Greedy Forwarding Routing Schemes using an Improved K-Means Approach for Wireless Sensor Networks

Reducing energy consumption in wireless sensor networks (WSNs) is one of the main ways to extend network lifetime since, in most cases, sensor nodes are battery-powered and are not rechargeable. One way to achieve this goal is to reduce the amount of redundant data sent to the base station (BS) through an aggregation operation carried out by the coordinating nodes. The clustering approach is considered as one of the most energy-efficient approaches for routing data in WSNs because in this approach the cluster-heads are responsible for the aggregation of the data packets, which reduces the amount of data sent to the BS. In this paper, we propose an approach based on an improved version of the K-Means method. This approach allows to find the appropriate number of clusters and generate clusters based on the radio communication of the nodes (RC). Moreover, to send data to the BS, we propose three greedy forwarding schemes. The first is a pure greedy forwarding (DKM-GF), the second is based on the distance and the residual energy of the relay nodes (DKM-GFE) and the third on the distance, the residual energy of the relay nodes and the energy dissipated to send data from a node to the forwarding node (DKM-GF2E). The proposed routing schemes have been implemented over MATLAB simulator. The results obtained show that our proposals bring significant improvements in terms of energy consumption, network lifetime and the number of packets sent to the base station compared to other protocols.

Energy-Aware Routing for Software-Defined Multihop Wireless Sensor Networks

In this paper, we propose an energy-aware routing algorithm and a control overhead reduction technique for prolonging the network lifetime of software-defined multihop wireless sensor networks (SDWSNs). This is an effort to optimize the energy consumption of WSNs that provide services to the Industrial Internet of Things (IIoT). A centralized controller grants a global view of the sensor network by introducing extra control overhead in the network, but this leads to extra energy costs. However, our new algorithm takes advantage of this global view and balances the network energy by selecting paths with the highest remaining energy level among multiple paths for each sensor node. We also identify key functions draining energy from the SDWSN and minimize their impact by implementing a data packet aggregation function, and minimizing the control overhead by keeping track of the sensor nodes' routing tables using a simple checksum function. We show that the proposed approach prolongs the network lifetime of the WSN by 6.5% on average compared to the standard shortest-path algorithm, and that the control overhead is reduced by approximately 12% while still maintaining a very high packet delivery ratio.

Context Information Aggregation Mechanism Based on Bloom Filters (CIA-BF) for High Performance Monitoring Applications of Internet of Things

Internet of Things (IoT) has become a popular technology in recent years. Different IoT applications such as traffic control, environment monitoring, etc. contain many sensor devices, routers, actuators, edge routers, and Base Stations (BS) which communicate with each other and send millions of data packets that need to be delivered to their destination nodes successfully to ensure the High-performance communication networks. IoT devices connect to the Internet using wired or wireless communication channels where most of the devices are wearable, which means people slowly move from one point to another or fast-moving using vehicles. How to ensure high performance of IoT data networks is an important research challenge while considering the limitation of some IoT devices that may have limited power resources or limited coverage areas. Many Kinds of research focus on how to customize routing protocols to be efficient for IoT devices. The traditional routing mechanisms utilized specific IP addresses to identify users while in IoT it is more beneficial to identify a group of users (things) based on any contexts, status, or values of their resources such as the level of their batteries (e.g., low, medium or high). While IoT devices have different characteristics, a multicasting mechanism to send one message to various groups of devices will not be efficient in IoT communication networks since the aggregation of packets is very difficult. Thus, it is useful to propose a mechanism that able to filter data packets that need to be sent to a specific group of devices. In this paper, we propose efficient context-aware addressing mechanism, which is based on bloom filters to increase the performance of IoT communication networks. A routing architecture is built based on bloom filters which store routing information. In our works, we reduce the size of routing information using a proposed aggregation mechanism which is based on connecting each group of IoT devices with an edge router which is hierarchically connected to an upper router after operating its bloom filter. Our simulation results show a significant improvement in the IoT performance metrics such as packets transmission delay, jitter the throughput, packets dropping ratio, and the energy consumption in comparison with well-known routing protocols of IoT such as Destination Sequenced Distance Vector routing protocol (DSDV), and Ad hoc On-demand Distance Vector routing protocol (AODV).

A review on P4-Programmable data planes: Architecture, research efforts, and future directions

Software Defined Networking (SDN) is a promising technology that provides flexibility, programmability, and network automation by shifting the network intelligence to the logically centralized controller. In SDN architecture, the controller maintains the global view of network topology; therefore the network management is efficient as compared to the traditional networks. Moreover, the cost of SDN devices is less due to the use of open source network operating system instead of proprietary and vendor-specific software. In spite of the flexibility offered by the SDN, OpenFlow enabled switches have a fixed behavior as specified in the datasheet of switch ASIC. They recognize fixed set of header fields according to the support of OpenFlow version. In addition, SDN is suffering from scalability and performance issues because SDN switches heavily dependent on the control plane to forward the packets which increases the data-control communication overhead. To resolve these issues, P4-Programmable data plane switches can be used. The analysis of review articles about SDN suggests insufficient focus on the data plane programmability. Therefore, this paper provides the comprehensive overview of domain-specific language (P4) for the programmability of the data plane. We have discussed the problems in the traditional SDN architecture and then, how these problems can be managed by the data plane programmability. Further, this study critically analyze the research articles based on the P4 programming language for network traffic monitoring, DDoS attack detection, load balancing, and packet aggregation and disaggregation. Finally, we have identified the research gaps and highlighted the open research challenges in the field of data plane programmability for the future directions.

Multihop Deterministic Energy Efficient Routing Protocol for Wireless Sensor Networks MDR

The inception of Wireless Sensor Networks (WSN) has brought convenience into many lives with uninterrupted wireless network. The nodes that transmit data consist of heterogeneous and battery equipped sensor nodes (SNs) that are deployed randomly for network surveillance. To manage the random deployment of nodes, clustering algorithms are used with efficient routing protocols. This results in aggregation and dropping of redundant data packets that enables flawless data transmission from cluster nodes to Base Station (BS) via Cluster Heads (CHs). In this paper, a dynamic and multi-hop clustering and routing protocol for thorough behavior analysis is proposed, taking distance and energy into consideration. This forms a smooth routing path from the cluster nodes, CHs, Sub-CHs to the BS. On comparing proposed process with the existing system, experimental analysis shows a significant enhancement in the performance of network lifetime, with improved data aggregation, throughput, as the protocol showing deterministic behavior while traversing the network for data transmission, we name this protocol as Multi-hop Deterministic energy efficient Routing protocol (MDR).

Securing an Accelerator-rich System from Flooding-based Denial-of-Service Attacks

Increasing demand for high performance and energy efficiency along with time-to-market pressures have led to a growing number of third-party accelerators in modern System-on-Chips (SoCs). However, the third-party accelerators may introduce vulnerabilities due to malicious intent or elusive design bugs that escape through verification processes. These vulnerabilities can be exploited by various attackers which can corrupt the entire system. Flooding is one such attack that is triggered by a malicious third-party accelerator to obstruct on-chip network communication by injecting useless packets leading to Denial-of-Service. To secure accelerator-rich SoCs from flooding attacks, we propose a two-step attack detection framework that leverages machine learning (ML) models to detect an attack scenario. The ML-based solution along with hierarchical feature data aggregation and feature packet prioritization provides an accurate attack detection with minimal performance overheads. Experimental evaluations with real accelerator benchmarks show the effectiveness of our framework achieving a detection accuracy of up to 97 % across various ML classifiers.

A 6LoWPAN OPNET simulation model for machine‐to‐machine communications

AbstractThe low‐power short‐range networks have gained prevalence in research fields such as machine‐to‐machine communications and the Internet of things. Given the large number of devices that may exist, the IPv6 over low‐power wireless personal area networks (6LoWPAN) standard is expected to be widely used. Although Contiki, NS‐3, and OMNeT++ have developed the 6LoWPAN model, it is still not available in optimized network engineering tools (OPNET) because it is extremely difficult to interface the built‐in IP module with the customized modules in OPNET. To bridge this gap, we first developed a preliminary 6LoWPAN model and implemented the header compression and header restoration functions to handle the incoming and outgoing packets in OPNET. To further improve the system performance, we also proposed an algorithm that aggregates packets, reduces intranetwork collisions and increases the packet delivery ratio. The model and algorithm in this work are free to download, so researchers from the OPNET community can easily extend this work for their own research in the future.

A Novel Packet Aggregation Mechanism for Enhancing VoIP Performance on IEEE 802.11 Wireless Mesh Networks

In 802.11 Wireless Mesh Network (WMN), bandwidth will be wasted much for transferring VoIP flows since each voice frame must contain relatively large amount of protocol data. “Packet Aggregation” mechanism can be applied to merge the voice data of multiple VoIP flows into one frame for transmission. It reduces the waste on bandwidth and increases the maximum number of successful VoIP calls. In addition, the mechanism “MCF controlled channel access” (MCCA) defined in 802.11 standard can be used to obtain better QoS than adopting default EDCA mechanism. In MCCA, mesh stations which wants to transfer VoIP flows can reserve time intervals of the medium for transmission and this reservation will be advertised to their neighbors. It is why MCCA causes less medium contentions than EDCA. In this paper, a mechanism to transfer VoIP flows in IEEE 802.11 WMN by MCCA with packet aggregation scheme is proposed. The effectiveness of the proposed mechanism is shown by simulation results. In addition, the problem named as Routing-Packet Aggregation / De-aggregation-Scheduling optimization problem (abbr. RPADS problem) derived from the proposed mechanism is also studied. A heuristic algorithm for RPADS problem to maximize the total number of supported calls is also proposed.