Message Delivery Ratio Research Articles

Design and Simulation of Efficient Dynamic Data Forwarding Protocol towards Route Optimization in VANET Infrastructure

The VANET, which consists of the Internet and the Internet of Things (IoT), has recently been implemented with the Internet of Vehicles (IoV). Through the use of a car network and an AdHoc approach, it provides the user with environmental traffic information. Combining the networks of cars, known as VANETs, allows for infrastructure-free data transfer, particularly for entertainment and emergency vehicle notification. The data or packet delivery ratio, data communication latency, data transmission faults, and details of vehicle collisions are among the traffic information provided by the internet of vehicles. In this work, an unmanned aerial vehicle (UAV) is used to solve the problem of route optimisation in VANET topologies for effective data transfer. Many routing protocols are used to improve the effectiveness of the packet or data routing process. In order to alleviate the routing issue and generate an effective way for efficient data transfer with strong network stability, the Optimised Link State Routing (OLSR) Protocol is used in this study with energy-saving techniques on many parameters. To evaluate the efficacy of the suggested routing technique on various network sizes, extensive simulations are carried out on the NS2 simulator with various network parameters. When compared to traditional routing protocols along UAV-based protocols for data transmission, the performance results of the suggested data routing solution employing OLSR protocol achieve higher efficient pathways. Ultimately, the suggested routing system produces superior outcomes in terms of message throughput, message delivery ratio, latency and network overhead on comparing with existing routing protocols.

CR-5: Resource optimization opportunistic network routing algorithm based on node dynamic attributes

The opportunistic network routing algorithms are the core technology of intermittent communication of mobile nodes in opportunistic networks. However, the existing researches on opportunistic network routing algorithms mainly focus on how to improve the message delivery ratio and reduce the route overhead ratio, and often neglect managing energy consumption and cache usage of node. This results in problems such as communication chain easy to interruption and congestion control instability in opportunity networks. To solve the above problems, this paper proposes CR-5: resource optimization opportunistic network routing algorithm based on node dynamic attributes. CR-5 comprehensively considers node dynamic attributes such as historical encounter information, resource availability, and node social input degree, defines node communication relay degree as the basis for selecting relay nodes, and realizes node energy balance and cache optimization. CR-5 tends to choose relay nodes with strong communication ability, which solves the problem of communication chain easy to interruption to some extent. CR-5 also enhances the resource management and message processing ability of nodes through energy balance and cache optimization, reduces the phenomenon that some nodes process too many messages, which solves the problem of congestion control instability to some extent. Simulation results show that in opportunistic networks with low node initial cache, the CR-5 algorithm greatly improves the message delivery ratio and the node average remaining energy, and significantly reduces the route overhead ratio.

Block chain based IAS protocol to enhance security and privacy in cloud computing

Cloud computing has become increasingly popular for data storage and processing, but security and privacy remain major concerns due to the potential for malicious attacks on wireless and mobile communication networks. In order to address these issues, researchers have proposed an IAS protocol that incorporates identity, access control, and secure authentication. To ensure the authenticity and security of data transmission in cloud computing, the proposed IAS protocol is implemented on top of blockchain technology. This allows for decentralized key management for recovery and revocation, as well as identity verification. To evaluate the effectiveness of this approach, the proposed model using Block Chain based Identity Management, Access Control and Secure Sharing (BC-IAS) is simulated on the cloud environment. The simulation assesses primary performance key metrics, including Data Access Rate, Message Delivery Ratio, End to End Delay and Energy consumption. Overall, the proposed BC-IAS protocol on top of blockchain technology shows promise for enhancing security and privacy in cloud computing. The proposed BC-IAS protocol on top of blockchain technology presents a promising solution for enhancing the security and privacy of cloud computing. The decentralized nature of blockchain technology ensures that data is stored in a tamper-proof and transparent manner, while the use of smart contracts allows for automated enforcement of access control policies. Moreover, the incorporation of identity verification and secure authentication ensures that only authorized users can access sensitive data, reducing the risk of data breaches and cyber-attacks.

Enhance Security and Privacy in VANET Based Sensor Monitoring and Emergency Services

VANET performs analysis of patient records and sends security warnings to the carer through VANET so that they may provide urgent assistance while keeping patient data safe. Threat actors might potentially access data packets that go between biological sensors and smart ambulances in the vehicular network. When healthcare professionals use a VANET, they run the risk of receiving inaccurate or delayed data as a result of assaults like the Sybil attack, denial of service attacks, and impersonation attacks. As a result, protecting people’s personal information and data has become an important task for academics. In this research, we propose the use of an Urbanized Block Chain Key Agreement Protocol (UB-KAP) based on a one-way hash chain model to increase protections for individual privacy and data integrity in VANET-based healthcare networks. The messages include timestamps in case the messages that have already expired cause excessive delays. The beacons’ packet classification mechanism separates them into benign and harmful emergency signals to speed up response times. The suggested model is tested by road traffic simulation using SUMO (Simulation of Urban Mobility). Data collection per user, message delivery ratio, total data gathered, delay, and energy usage are all included in the model’s overall evaluation.

Double Q-learning based routing protocol for opportunistic networks

Opportunistic Delay Tolerant Networks also referred to as Opportunistic Networks (OppNets) are a subset of wireless networks having mobile nodes with discontinuous opportunistic connections. As such, developing a performant routing protocol in such an environment remains a challenge. Most research in the literature have shown that reinforcement learning-based routing algorithms can achieve a good routing performance, but these algorithms suffer from under-estimations and/or over-estimations. Toward addressing these shortcomings, in this paper, a Double Q-learning based routing protocol for Opportunistic Networks framework named Off-Policy Reinforcement-based Adaptive Learning (ORAL) is proposed, which selects the most suitable next-hop node to transmit the message toward its destination without any bias by using a weighted double Q-estimator. In the next-hop selection process, a probability-based reward mechanism is involved, which considers the node’s delivery probability and the frequency of encounters among the nodes to boost the protocol’s efficiency. Simulation results convey that the proposed ORAL protocol improves the message delivery ratio by maintaining a trade-off between underestimation and overestimation. Simulations are conducted using the HAGGLE INFOCOM 2006 real mobility data trace and synthetic model, showing that when time-to-live is varied, (1) the proposed ORAL scheme outperforms DQLR by 14.05%, 9.4%, 5.81% respectively in terms of delivery probability, overhead ratio and average delay; (2) it also outperforms RLPRoPHET by 16.17%, 9.2%, 6.85%, respectively in terms of delivery ratio, overhead ratio and average delay.

DewDrone: Dew Computing for Internet of Drone Things

Unstable internet connectivity in aerial interconnection is challenging for the Internet of drone Things. Introducing the low power edge device and caching methodology opens a new challenge to developing an independent computing and communication application for smart cities, the rural sector, industry, and society 4.0. This author proposes a dew-cloud computing framework amalgamated with the UAV networks known as “DewDrone.” We engineered an opportunistic communication framework for unreliable and intermittent network connectivity. We analyzed the dew message transfer response, and caching performance has been measured in a resource constrain hardware testbed. The results show the 91.4% message delivery ratio within a dew buffer size of 150 MB with a minimum latency of 20.04 ms.

LoCaL: Link‐optimized cone‐assisted location routing in flying ad hoc networks

SummaryRecently, flying ad hoc networks (FANETs) has become a core research area in wireless networks that involves multiple unmanned aerial vehicles (UAVs). It is widely used in modern warfare for surveillance, monitoring and reconnaissance. The routing in FANETs poses a more significant challenge due to limited energy and frequent link disconnection between the UAVs. Consequently, an effective route is always required to ensure data transmission between UAVs. Therefore, this research proposes a link‐optimized cone‐assisted location (LoCaL) routing protocol for FANETs. The main goal of the proposed LoCaL is to enhance the link duration between the UAVs in which a source selects a forwarding UAV from a given set of neighbours by estimating the residual energy, link duration time and safety degree parameters. Proposed LoCaL provides better stability and less frequent route breaks between source and destination. Further, the mathematical formulation of the proposed approach is presented through the utility function to enhance the route stability by selecting all those relay UAVs in the cone‐shaped request zone, which reduces the routing overhead in discovering the route. Finally, the performance of the LoCaL has been presented through key indicators such as energy consumption, routing overhead, message delivery ratio, network lifetime and delay compared to the existing approaches.

VP-CAST: Velocity and Position-Based Broadcast Suppression for VANETs

In the vehicular ad hoc networks (VANETs), minimizing the broadcast storm that arises due to message rebroadcast during emergency message dissemination in extremely mobile environments under sparse or dense networks is a significant challenge. Proper selection of rebroadcasting vehicles guarantees acceptable end-to-end delay, high delivery ratio, and efficient bandwidth utilization. To date, many protocols have been proposed to select an appropriate rebroadcasting vehicles based on vehicle position information only. However, such approaches neglect the fact that both vehicle velocity and position information can be utilized efficiently to alleviate rebroadcast message collisions and control bandwidth consumption. In this work, we present a new broadcast suppression protocol, named, velocity and position-based broadcast suppression for VANETs (VP-CAST), which can work in both sparse and dense network situations. VP-CAST does rely on periodic beacon messages, rather the position and velocity information of broadcasting vehicle are included in a broadcast message. Moreover, the transmission range of broadcasting vehicle is divided into dynamic time slots based on velocity and position information of broadcasting and receiving vehicles.The proposed scheme assigns shorter and dynamic waiting time to the vehicles moving at high velocities and located farther from the sender vehicle that eventually reduces both the message re-transmission delay and the number of rebroadcasting vehicles. The proposed protocol is compared with the DV-CAST in terms of end-to-end delay, message delivery ratio, and message overhead.

An intelligent edge enabled 6G‐flying ad‐hoc network ecosystem for precision agriculture

AbstractUnmanned aerial vehicle based precision agriculture is a predominant research area. The modern flying ad‐hoc network leverages the advanced low latency vehicular communication and intelligent computing paradigms that help the ecosystem to grow up to the next level. In this work, we propose an ecosystem for precision agriculture that leverages the use of the opportunistic MQTT protocol in an edge‐enabled intelligent drone network for sensing and performing crop prediction using an intelligent ensemble machine learning model. The proposed approach leverages the edge computing system that requires low energy devices and also exploits the ultra‐low latency opportunistic message transfer methodology. The experimental results show the maximum of 0.9 message delivery ratio and a minimum of 600 ms latency is achieved by opportunistic MQTT protocol in an ultra‐low latency sparse network scenario. A weighted ensemble model is deployed onto the edge enabled devices or the drones. An accuracy of 96.5% is achieved in predicting the type of crops that can be grown in the soil about the selected area of interest.

Noise-Based-Protection Message Dissemination Method for Insecure Opportunistic Underwater Sensor Networks

Opportunistic Underwater Sensor Networks (OUSNs) are deployed for various underwater applications, such as underwater creature tracking and tactical surveillance. In an OUSN invaded by some eavesdroppers, the data messages disseminated by sensor nodes are probably stolen (captured and cracked) by the eavesdroppers. The data messages are disseminated through acoustic waves which could be altered by the environmental noises, i.e., the acoustic waves containing data messages could be superimposed by the environmental noises. To protect the data messages from being stolen by eavesdroppers and guarantee the required delivery ratio of data messages, we propose a Noise-based-protection Message Dissemination Method (NMDM). In NMDM, the acoustic waves containing data messages are superposed by the environmental noises and converted into some pseudo data messages. The environmental noises around source nodes are identified, encoded, and encrypted into some noise messages. Then, the pseudo data messages and noise messages are individually disseminated to the sink node. Such mechanism makes the eavesdroppers difficult to steal the data messages. Besides, the required delivery ratio of data messages is achieved by measuring the similarities between the nodes and the sink node, i.e., the pseudo data messages and noise messages are preferentially disseminated to the nodes with larger similarities to the sink node. Finally, simulation results demonstrate the superior performance of NMDM. NMDM can reduce the theft ratio of data messages and guarantee the required delivery ratio of data messages effectively.

Speed and Position Aware Dynamic Routing for Emergency Message Dissemination in VANETs

Vehicular Ad hoc Networks (VANETs) can help reduce traffic-related accidents by broadcasting Emergency Messages (EMs) in advance between vehicles. Due to the high-speed mobility of VANETs and attenuation of the wireless signal, reliable and fast transmission of EMs is a challenging task. Such as the chosen next-hop vehicle may have driven away from the neighborhood of the sender before receiving the EM, and rerouting may increase the delay when the EMs encounter transmission failure. To this end, we propose a Speed and Position aware Dynamic Routing (SPDR) for EM dissemination in VANETs. First, we introduce a speed metric dynamic greedy routing to provide a dynamic hop-by-hop rebroadcast of the EM. SPDR dynamically shrinks the Routing Decision Area (RDA) range based on the velocity variance of candidate neighbors and prioritizes the farthest vehicle in the shrunk RDA as the optimal next-hop, enhancing the reliable transmission of EMs. Then, we present a collaborative forwarding strategy to enable candidate neighbors to collaborate in communication. In case of transmission failure, SPDR elects the candidate vehicle close to the destination as the forwarder to reduce rerouting. Simulations in a practical motorway scenario using NS-2 and VanetMobiSim show that SPDR outperforms the existing protocols in terms of message delivery ratio, network throughput, and average dissemination delay.

A Dynamic Resource-Aware Routing Protocol in Resource-Constrained Opportunistic Networks

Recently, Opportunistic Networks (OppNets) are considered to be one of the most attractive developments of Mobile Ad Hoc Networks that have arisen thanks to the development of intelligent devices. OppNets are characterized by a rough and dynamic topology as well as unpredictable contacts and contact times. Data is forwarded and stored in intermediate nodes until the next opportunity occurs. Therefore, achieving a high delivery ratio in OppNets is a challenging issue. It is imperative that any routing protocol use network resources, as far as they are available, in order to achieve higher network performance. In this article, we introduce the Resource-Aware Routing (ReAR) protocol which dynamically controls the buffer usage with the aim of balancing the load in resource-constrained, stateless and non-social OppNets. The ReAR protocol invokes our recently introduced mutual information-based weighting approach to estimate the impact of the buffer size on the network performance and ultimately to regulate the buffer consumption in real time. The proposed routing protocol is proofed conceptually and simulated using the Opportunistic Network Environment simulator. Experiments show that the ReAR protocol outperforms a set of well-known routing protocols such as EBR, Epidemic MaxProp, energy-aware Spray and Wait and energy-aware PRoPHET in terms of message delivery ratio and overhead ratio.

Message piece dissemination approach for opportunistic underwater sensor network invaded by underwater spy‐robots

AbstractOpportunistic underwater sensor network (OUSN) is deployed for various underwater applications, such as underwater creatures tracking and tactical surveillance. Particularly, the OUSN in military applications may be invaded by some underwater spy‐robots termed eavesdroppers. The eavesdroppers could move around some OUSN nodes and eavesdrop on their communication channels silently, and these eavesdropping actions are difficult to be perceived by OUSN nodes. To reduce the theft ratio of data messages and guarantee the required delivery ratio of data messages, we conceive the idea that each data message is encoded into several message pieces, and then the message pieces are disseminated to sink node individually. Besides, a lightweight encryption method is adopted to encrypt the message pieces before the dissemination. Such mechanism can protect the data messages from being stolen by eavesdroppers effectively. In this article, we propose a message piece dissemination approach (MPDA) for the OUSN invaded by some underwater spy‐robots. In MPDA, OUSN nodes disseminate the held message pieces to some selected neighboring nodes at each time slot, and a data message is considered to be delivered when all pieces of this data message have been delivered to the sink node. Extensive simulations and comparisons demonstrate the preferable performance of MPDA, that is, MPDA can reduce the theft ratio of data messages and guarantee the required delivery ratio of data messages.

Analysis of Epidemic, PROPHET and Spray and Wait Routing Protocols in the Mobile Opportunistic Networks

Background: The Opportunistic Mobile Networks (OMNs) are a type of Mobile Adhoc Networks (MANETs) with Delay-Tolerant Network (DTN) features, where the sender to receiver connectivity never exists most of the time, due to dynamic nature of the nodes and the network partition. The real use of OMNs is to provide connectivity in challenged environments. Methods: The paper presents the detailed analysis of three routing protocols, namely Epidemic, PROPHET and Spray and Wait, against variable size of the messages and the Time To Live (TTL) in the networks. The key contribution of the paper is to explore routing protocols with mobility models for the dissemination of data to the destination. Routing uses the store-carry-forward mechanism for message transfer and network has to keep compromise between message delivery ratio and delivery delay. Results: The results are generated from the experiments with Opportunistic Network Environment (ONE) simulator. The performance is evaluated based on three metrics, the delivery ratio, overhead ratio and the average latency. The results show that the minimum message size (256 KB) offers better performance in the delivery than the larger message size (1 MB). It has also been observed that with the epidemic routing, since there are more message replicas, which in turn increase the cost of delivery, so with a smaller message, the protocol can reduce the overhead ratio with a high proportion. Conclusion: The average latency observed increases with the increase of the TTL of the message in three protocols with variation of the message size from 256KB to 1 MB.

Activity-based routing algorithm in opportunistic mobile social networks

In opportunistic mobile social networks, nodes are clustered according to their interests or hobbies and take part in different activities regularly. We delve into the temporal and spatial mobility characteristics of network nodes and put forward an activity-based message opportunistic forwarding algorithm. The main idea of the algorithm is that we choose different message forwarding methods according to the situation of nodes participating in activities. If the source node and the destination node are both attend in the same activities, we select the best relay node which has the biggest delivery probability. While the source node and the destination node are not in the same activities at the same time, we need to find the optimal path which owns highest indirect delivery probability, and messages will be transmitted through the optimal path. The simulation results show that the proposed routing algorithm can not only improve the successful delivery ratio of messages but also reduce the network delay and the network overhead obviously, in comparison with the classical opportunistic routing algorithms, such as community-aware message opportunistic transmission algorithm, community-based message transmission scheme algorithm, PRoPHET, Epidemic algorithm, and interest characteristic probability prediction algorithm.

Probability and topic‐based data transmission protocol

SummaryIn the fog computing (FC) models, a fog node supports not only routing functions but also application processes. By the application processes, output data are calculated on input data from sensors and other nodes and sent to target fog nodes which can calculate on the output data. In this article, we consider the mobile topic‐based publish/subscribe fog computing (MPSFC) model where mobile fog nodes communicate with one another by publishing and subscribing messages in wireless networks. Subscription topics of a fog node denote input data on which the node can calculate output data. Publication topics of a message show data carried by the message. In the topic‐based data transmission (TBDT) protocol proposed in our previous studies, while a fewer number of messages are transmitted, the delivery ratio of messages is smaller than the epidemic routing protocol. In this article, we newly propose a pair of time‐to‐live‐based data transmission (TTLBDT) and probability and topic‐based data transmission (PTBDT) protocols in order to increase the delivery ratio. If another node is found in the communication range, a fog node forwards messages to the node. Even if the node is not a target node, the node receives the message with some probability in the PTBDT protocol. In the evaluation, we show the delivery ratios in the TTLBDT and PTBDT protocols are larger than the TBDT protocol. In addition, we show the number of messages exchanged in the PTBDT protocol is smaller than the epidemic routing protocol.

An Optimized and Efficient Routing Protocol Application for IoV

IoV is the latest application of VANET and is the alliance of Internet and IoT. With the rapid progress in technology, people are searching for a traffic environment where they would have maximum collaboration with their surroundings which comprise other vehicles. It has become a necessity to find such a traffic environment where we have less traffic congestion, minimum chances of a vehicular collision, minimum communication delay, fewer communication errors, and a greater message delivery ratio. For this purpose, a vehicular ad hoc network (VANET) was devised where vehicles were communicating with each other in an infrastructureless environment. In VANET, vehicles communicate in an ad hoc manner and communicate with each other to deliver messages, for infotainment purposes or for warning other vehicles about emergency scenarios. Unmanned aerial vehicle- (UAV-) assisted VANET is one of the emerging fields nowadays. For VANET’s routing efficiency, several routing protocols are being used like optimized link state routing (OLSR) protocol, ad hoc on-demand distance vector (AODV) routing protocol, and destination-sequenced distance vector (DSDV) protocol. To meet the need of the upcoming era of artificial intelligence, researchers are working to improve the route optimization problems in VANETs by employing UAVs. The proposed system is based on a model of VANET involving interaction with aerial nodes (UAVs) for efficient data delivery and better performance. Comparisons of traditional routing protocols with UAV-based protocols have been made in the scenario of vehicle-to-vehicle (V2V) communication. Later on, communication of vehicles via aerial nodes has been studied for the same purpose. The results have been generated through various simulations. After performing extensive simulations by varying different parameters over grid sizes of 300 × 1500 m to 300 × 6000 m, it is evident that although the traditional DSDV routing protocol performs 14% better than drone-assisted destination-sequenced distance vector (DA-DSDV) when we have number of sinks equal to 25, the performance of drone-assisted optimized link state routing (DA-OLSR) protocol is 0.5% better than that of traditional OLSR, whereas drone-assisted ad hoc on-demand distance vector (DA-AODV) performs 22% better than traditional AODV. Moreover, if we increase the number of sinks up to 50, it can be clearly seen that the DA-AODV outperforms the rest of the routing protocols by up to 60% (either traditional routing protocol or drone-assisted routing protocol). In addition, for parameters like MAC/PHY overhead and packet delivery ratio, the performance of our proposed drone-assisted variants of protocols is also better than that of the traditional routing protocols. These results show that our proposed strategy performs better than the traditional VANET protocols and plays important role in minimizing the MAC/PHY and enhancing the average throughput along with average packet delivery ratio.

Heterogeneous Mobile Networking for Lightweight UAV Assisted Emergency Communication

Due to the frequent natural disasters in recent two years, UAV assisted disaster networks have attracted attention due to the flexible information storage and favorable computation capacity in technical rescue. The previous studies concentrate on dynamically optimizing the service coverage to improve the system performance. However, the continually changing of energy cost, time cost, and the social connections between users are not jointly considered in previous studies. In this paper, we propose a social relationship-based timeliness aware message splitting scheme for the energy-friendly UAV assisted delay tolerant networks. Firstly, we put forward our social network based splitting optimization problem and use social network closeness and message's decaying with time to quantify the messages' value. Next, a social optimization copy splitting algorithm (SOCS) is designed to guarantee the lower expected delay and higher message delivery ratio through UAV assisted interesting areas (IAs). Finally, the extensive simulations show the optimality of the proposed SOCS algorithm using the enhanced social relationship based forwarding scheme.

BiRep: A Reputation Scheme to Mitigate the Effects of Black-Hole Nodes in Delay-Tolerant Internet of Vehicles.

Delay-tolerant networking (DTN) enables communication in disruptive scenarios where issues such as sparse and intermittent connectivity, long and variable delays, high latency, high error rates, or no end-to-end connectivity exist. Internet of Vehicles (IoV) is a network of the future in which integration between devices, vehicles, and users will be unlimited and universal, overcoming the heterogeneity of systems, services, applications, and devices. Delay-tolerant internet of vehicles (DT-IoV) is emerging and becoming a popular research topic due to the critical applications that can be realized, such as software or map update dissemination. For an IoV to work efficiently, a degree of cooperation between nodes is necessary to deliver messages to their destinations. However, nodes might misbehave and silently drop messages, also known as a black-hole attack, degrading network performance. Various solutions have been proposed to deal with black-hole nodes, but most are centralized or require each node to meet every other node. This paper proposes a decentralized reputation scheme called BiRep that identifies and punishes black-hole nodes in DT-IoV. BiRep is tested on the Prophet routing protocol. Simulation results show excellent performance in all scenarios, comparable or better to other reputation schemes, significantly increasing the delivery ratio of messages.

EA-RDSP: Energy Aware Rapidly Deployable Wireless Ad hoc System for Post Disaster Management

In post disaster scenarios such as war zones floods and earthquakes, the cellular communication infrastructure can be lost or severely damaged. In such emergency situations, remaining in contact with other rescue response teams in order to provide inputs for both headquarters and disaster survivors becomes very necessary. Therefore, in this research work, a design, implementation and evaluation of energy aware rapidly deployable system named EA-RDSP is proposed. The proposed research work assists the early rescue workers and victims to transmit their location information towards the remotely located servers. In EA-RDSP, two algorithms are proposed i.e., Hop count Assignment (HCA) algorithm and Maximum Neighbor Selection (MNS) algorithm. The EA-RDSP contains three types of nodes; the client node sends information about casualty in the disaster area to the server, the relay nodes transmit this information from client node to server nodes via multi-hop transmission, the server node receives messages sent by client node to alert rescue teams. The EAM-RDSP contains three types of nodes; the client node sends information about casualty in the disaster area to the server, the relay nodes transmit this information from client node to server nodes via multi-hop transmission, the server node receives messages sent by client node to alert rescue teams. The proposed EA-RDSP scheme is simulated using NS-2 simulator and its performance is compared with existing scheme in terms of end-to-end delay, message delivery ratio, network overhead and energy consumption.