Optimal Packet Research Articles

Optimal packet length for throughput maximisation in mmWave WPANs using directional antennas

ABSTRACTIn this paper, the effect of packet length on the throughput is studied in millimetre-wave band based Wireless Personal Area Networks. A device has a finite queue and uses a directional antenna. A Markov chain model is considered for no-ACK mode in directional carrier sense multiple access with collision avoidance under error-prone channel and saturation environments. The features of Medium Access Control of IEEE 802.15.3c such as freezing of backoff counter are considered in the model. The effects of directional antennas and bit error rate are also considered. The throughput and delay including queuing delay are analysed, and the optimal packet length is derived by analysing the throughput. The numerical results show that the longer packets are preferred in the environment that the number of contending devices is small and the beamwidth is narrow. In addition, the optimal packet length maximising throughput is derived, which depends on several parameters such as beamwidth, the number of devices, and the bit error rate. The obtained results provide the criterion in determining the packet length for effective resource utilisation.

A Genetic Algorithm for the Generation of Packetization Masks for Robust Image Communication.

Image interleaving has proven to be an effective solution to provide the robustness of image communication systems when resource limitations make reliable protocols unsuitable (e.g., in wireless camera sensor networks); however, the search for optimal interleaving patterns is scarcely tackled in the literature. In 2008, Rombaut et al. presented an interesting approach introducing a packetization mask generator based in Simulated Annealing (SA), including a cost function, which allows assessing the suitability of a packetization pattern, avoiding extensive simulations. In this work, we present a complementary study about the non-trivial problem of generating optimal packetization patterns. We propose a genetic algorithm, as an alternative to the cited work, adopting the mentioned cost function, then comparing it to the SA approach and a torus automorphism interleaver. In addition, we engage the validation of the cost function and provide results attempting to conclude about its implication in the quality of reconstructed images. Several scenarios based on visual sensor networks applications were tested in a computer application. Results in terms of the selected cost function and image quality metric PSNR show that our algorithm presents similar results to the other approaches. Finally, we discuss the obtained results and comment about open research challenges.

Cross Layered Network Condition Aware Mobile-Wireless Multimedia Sensor Network Routing Protocol for Mission Critical Communication

The high pace emergence in wireless technologies have given rise to an immense demand towards Quality of Service (QoS) aware multimedia data transmission over mobile wireless multimedia sensor network (WMSN). Ensuring reliable communication over WMSN while fulfilling timely and optimal packet delivery over WMSN can be of great significance for emerging IoT ecosystem. With these motivations, in this paper a highly robust and efficient cross layered routing protocol named network condition aware mobile-WMSN routing protocol (NCAM-RP) has been developed. NCAM-RP introduces a proactive neighbour table management, congestion awareness, packet velocity estimation, dynamic link quality estimation (DLQE), and deadline sensitive service differentiation based multimedia traffic prioritization, and multi-constraints based best forwarding node selection mechanisms. These optimization measures have been applied on network layer, MAC layer and the physical layer of the protocol stack that eventually strengthen NCAM-RP to enable QoS-aware multimedia data transmission over WMSNs. The proposed NCAM-RP protocol intends to optimize real time mission critical (even driven) multimedia data (RTMD) transmission while ensuring best feasible resource allocation to the non-real time (NRT) data traffic over WMSNs. NCAM-RP has outperform RPAR based routing scheme in terms of higher data delivery, lower packet drops and deadline miss ratio. It signifies that NCAM-RP can ensure minimal retransmission that eventually can reduce energy consumption, delay and computational overheads. Being the mobility based WMSN protocol, NCAM-RP can play significant role in IoT ecosystem.

On the packet allocation of multi-band aggregation wireless networks

The use of heterogeneous networks with multiple radio access technologies (RATs) is a system concept that both academia and industry are studying. In such system, integrated use of available multiple RATs is essential to achieve beyond additive throughput and connectivity gains using multi-dimensional diversity. This paper considers an aggregation module called opportunistic multi-MAC aggregation (OMMA). It resides between the IP layer and the air interface protocol stacks, common to all RATs in the device. We present a theoretical framework for such system while considering a special case of multi-RAT systems, i.e., a multi-band wireless LAN (WLAN) system. An optimal packet distribution approach is derived which minimizes the average packet latency (the sum of queueing delay and serving delay) over multiple bands. It supports multiple user terminals with different QoS classes simultaneously. We further propose a packet scheduling algorithm, OMMA Leaky Bucket, which minimizes the packet end-to-end delay, i.e., the sum of average packet latency and average packet reordering delay. We also describe the system architecture of the proposed OMMA system, which is applicable for the general case of the multi-RAT devices. It includes functional description, discovery and association processes, and dynamic RAT update management. We finally present simulation results for a multi-band WLAN system. It shows the performance gains of the proposed OMMA Leaky Bucket scheme in comparison to other existing packet scheduling mechanisms.

Packet-Size Optimization for Multiple-Input Multiple-Output Cognitive Radio Sensor Networks-Aided Internet of Things

The determination of optimal packet size (OPS) for a cognitive radio-assisted sensor networks (CRSNs) architecture is non-trivial. State of the art in this area describes various complex techniques to determine OPS for CRSNs. However, it is observed that under high interference from the surrounding users, it is not possible to determine a feasible OPS of data transmission under the simple point-to-point CRSN topology. This is contributed primarily to the peak transmit power constraint of the cognitive nodes. To address this specific challenge, this paper proposes a multiple-input multiple output-based CRSNs (MIMO-CRSNs) architecture for futuristic technologies, such as Internet of Things and machine-to-machine communications. A joint optimization problem is formulated, considering network constraints, such as the overall end-to-end latency, interference duration caused to the non-cognitive users, average BER, and transmit power. We propose our Algorithm 1 based on the generic exhaustive search technique to solve the optimization problem. Furthermore, a low complexity suboptimal Algorithm 2 based on solving classical Karush–Kuhn–Tucker conditions is proposed. These algorithms for MIMO-CRSNs are implemented in conjunction with two different channel access schemes. These channel access schemes are time-slotted distributed cognitive medium access control denoted as MIMO-DTS-CMAC and CSMA/CA-assisted centralized common control channel-based cognitive medium access control denoted as MIMO-CC-CMAC. Simulations reveal that the proposed MIMO-CRSN outperforms the conventional point-to-point CRSN in terms of overall energy consumption. Moreover, the proposed Algorithm 1 and Algorithm 2 show a perfect match, and the implementation complexity of Algorithm 2 is less than Algorithm 1 . Algorithm 1 takes almost 680 ms to execute and provides OPS value for a given number of users, whereas Algorithm 2 takes 4–5 ms on average to find the OPS for the proposed MIMO-CRSN framework.

Optimal Cognitive Access and Packet Selection Under a Primary ARQ Process via Chain Decoding

This paper introduces a novel technique that enables access by a cognitive secondary user (SU) to a spectrum occupied by an incumbent primary user (PU) that employs Type-I hybrid automatic retransmission request (ARQ). The technique allows the SU to perform selective retransmissions of SU data packets, whose transmission previously failed. The temporal redundancy introduced by the PU ARQ protocol and by the selective retransmission process of the SU can be exploited by the SU receiver to perform interference cancellation (IC) over multiple transmission slots, thus creating a “clean” channel for the decoding of the concurrent SU or PU packets. The chain decoding (CD) technique is initiated by a successful decoding operation of an SU or a PU packet and proceeds by an iterative application of IC as previously buffered packets become decodable and their interference can be removed, thus making it possible to recover the concurrent data packets, and so on, until no more packets are decodable. Based on this scheme, an optimal policy is designed that maximizes the SU throughput under a constraint on the average long-term PU performance. The optimality of the CD protocol is proved, which determines which packet the SU should send at any given time, based on four basic rules. Moreover, a decoupling principle is proved, which establishes the optimality of decoupling the secondary access strategy from the CD protocol. Specifically, first , the SU access policy, optimized via dynamic programming, specifies whether the SU should access the channel or remain idle, based on a compact state representation of the protocol, and second , the CD protocol embeds four basic rules that are used to select the packet transmitted by the SU. It is shown numerically that CD outperforms by up to 35% other schemes considered in the literature, which do not employ retransmissions at the SU pair and thus do not exploit the full potentiality of IC.

Automating selection of optimal packet scheduling during VоIP-traffic transmission

The usage of various packet scheduling disciplines in computer networking devices as a mechanism to ensure the quality of service is described. Stages for selection of necessary parameters values of packet scheduling during VoIP-traffic transmission in computer networks are defined. VoIP-traffic was set as a research object because there are strict requirements of VoIP-applications to the network transmission parameters. With the aid of training and experimental simulation system the numerous experiments for parameters selection of the most common packet scheduling disciplines were carried out (FIFO, WFQ, non-preemptive priority queueing). The example that illustrates the ability to adjust the weighting coefficients of WFQ packet scheduling discipline is presented. Approximate analytical dependences are obtained and they will significantly reduce system administrators’ efforts to assess and modify the parameters of packet scheduling in network devices. A method of automating selection of the optimal packet scheduling discipline is formulated.

Energy optimal channel attempt rate and packet size for ALOHA based underwater acoustic sensor networks

In this paper, we investigate the energy efficiency and throughput of ALOHA based underwater acoustic sensor networks (UASNs). We derive closed form expressions for the channel attempt rate and packet length at which energy efficiency and throughput are maximized separately. Based on our results, we observe that the packet length that maximizes energy efficiency leads to deterioration of throughput and vice versa. Motivated by these observations, we consider a cross layer optimization problem with the objective of maximizing the energy efficiency of the network, while meeting throughput criteria at the MAC layer and an SNR criteria at the PHY layer. With the aid of Karush---Kuhn---Tucker conditions, we derive closed form solutions for the optimal channel attempt rate and packet length that satisfy the desired objectives. For the analysis, we consider underwater acoustic channel specific parameters such as spreading losses and distance dependent bandwidth. Extensive performance evaluation study of our approach proves that, judicious selection of the packet lengths as well as channel attempt rates by the sensor nodes can ameliorate the energy efficiency of UASN remarkably, while satisfying the throughput criterion.

Transmission Capacity of Clustered Ad Hoc Networks With Virtual Antenna Array

In this paper, a clustered ad hoc network with virtual antenna array is investigated. Considering the random distribution of the nodes in ad hoc networks, the nodes are modeled as a Poisson point process (PPP). Different from prior analyses, interference in the ad hoc network is taken into account. Outage probability and transmission capacity of a single-hop network are first derived, and the accuracy of the analytical results is verified by simulation results. It is found that the outage probability decays as $\Theta(\lambda_c^{-(2/\alpha)})$ , where $\lambda_c$ is the intensity of potential cooperative nodes, and $\alpha$ is the path-loss exponent. That is, the outage probability obeys an inverse- $\mbox{2}/\alpha$ law with the intensity of cooperative nodes $\lambda_c$ . Moreover, there exists a unique optimal packet transmission rate to maximize the transmission capacity, and the optimal rate is shown to be within a specific interval that is only related to a path-loss exponent. Finally, the analysis of transmission capacity is extended to a multihop network. The results show that multihop transmission is not beneficial to the transmission capacity, but it does improve the outage performance. The analytical results are meaningful and can provide theoretical guidance on the network design.

Packet assignment under resource constraints with D2D communications

D2D communications offer various benefits such as coverage extension and high energy efficiency. For example, a cluster of in-coverage devices can be recruited to relay packets for an out-of-coverage device. As the helper devices can be subject to varying relay costs and resource constraints, a sequence of packets need to be properly assigned among the helpers. In this article, we study the packet assignment problem from a mechanism design's perspective, taking into account the strategic interactions of self-interested helpers. Fundamental concepts in mechanism design are introduced for general readers to understand the background. Auctions are an important application of mechanism design and widely used in many fields. We develop a reverse auction mechanism, consisting of an allocation rule and a payment rule, to assign packets among helpers and determine payments based on their declared costs and resource constraints. As it is NP-hard to find an optimal packet assignment that minimizes the total cost, we use a low-complexity allocation rule, which performs closely to the optimal allocation on average. The payment rule implements the allocation rule in dominant strategies in which helpers disclose their true costs and resource constraints. This truthful revelation in turn justifies the allocation according to the helpers' declaration. Numerical analysis and simulations are conducted to evaluate the performance.

Optimal Packet Loss Rate Based Vertical Handoff Algorithm for Wireless Heterogeneous Networks

Optimal Packet Loss Rate Based Vertical Handoff Algorithm for Wireless Heterogeneous Networks

Flaw Diagnosis Technology for Remanufactured Motor Rotor Based on Optimal Wavelet Packet Shannon Entropy

Flaw Diagnosis Technology for Remanufactured Motor Rotor Based on Optimal Wavelet Packet Shannon Entropy

Packet Size Optimization for Cognitive Radio Sensor Networks Aided Internet of Things

Cognitive radio sensor networks (CRSNs) is the state-of-the-art communication paradigm for power constrained short range data communication. It is one of the potential technologies adopted for Internet of Things (IoT) and other futuristic machine-to-machine-based applications. Many of these applications are power constrained and delay sensitive. Therefore, CRSN architecture must be coupled with different adaptive and robust communication schemes to take care of the delay and energy efficiency at the same time. Considering the tradeoff that exists in terms of energy efficiency and overhead delay for a given data packet length, it is proposed to transmit the physical layer payload with an optimal packet size (OPS) depending on the network condition. Furthermore, due to the cognitive feature of CRSN architecture overhead energy consumption due to channel sensing and channel handoff plays a critical role. Based on the above premises, in this paper, we propose a heuristic exhaustive search-based Algorithm-1 and a computationally efficient suboptimal low complexity Karuh–Kuhn–Tucker (KKT) condition-based Algorithm-2 to determine the OPS in CRSN architecture using variable rate m-QAM modulation. The proposed algorithms are implemented along with two main cognitive radio assisted channel access strategies based on distributed time slotted-cognitive medium access control (DTS-CMAC) and centralized common control channel-based cognitive medium access control (CC-CMAC) and their performances are compared. The simulation results reveal that proposed Algorithm-2 outperforms Algorithm-1 by a significant margin in terms of its implementation time. For the exhaustive search-based Algorithm-1 the average time consumed to determine OPS for a given number of cognitive users is 1.2 s, while for KKT-based Algorithm-2, it is of the order of 5–10 ms. CC-CMAC with OPS is most efficient in terms of overall energy consumption but incurs more delay as compared to DTS-CMAC with OPS scheme.

On the Performance of HARQ-IR over Nakagami-m Fading Channels in Mobile Ad Hoc Networks

In this paper, outage performance of hybrid automatic repeat request (HARQ) with incremental redundancy over Nakagami-m fading channels in a mobile ad hoc network is analyzed. Different from prior analyses, both interlink interference and random distribution of the nodes are considered, which makes the analysis practical and challenging. Based on an orthogonal polynomial approximation, the probability distribution of the product of multiple shifted signal-to-interference-and-noise ratios (SINRs) and the outage probability are derived in closed forms. The impacts of various system parameters including the intensity of source nodes, the number of retransmissions and the packet rate on the outage probability are then studied thoroughly. The closed-form outage probability enables further analysis of a wide range of performance metrics and delay limited throughput (DLT) is particularly discussed here. It is found that a limited number of retransmissions is sufficient to achieve the maximum DLT. With the analytical results, the optimal packet rate to maximize the DLT is also found. To characterize the performance of the whole network, network DLT (NDLT), which is the maximum achievable aggregated DLT in a unit area under a certain outage constraint, is finally introduced. The scaling law of NDLT over the network density is revealed. Specifically, the NDLT scales linearly with the network density $\lambda$ when the network is sparse, while it follows the $(1 - \frac{\alpha }{2})$ power law over the network density where $\alpha$ is the path loss exponent when the network is dense.

Channel-Adaptive Packetization Policy for Minimal Latency and Maximal Energy Efficiency

This article considers the problem of delay optimal bundling of the input symbols into transmit packets in the entry point of a wireless sensor network such that the link delay is minimized under an arbitrary arrival rate and a given channel error rate. The proposed policy exploits the variable packet length feature of contemporary communications protocols in order to minimize the link delay via packet length regularization. This is performed through concrete characterization of the end-to-end link delay for zero error tolerance system with First Come First Serve (FCFS)queuing discipline and Automatic Repeat Request (ARQ) retransmission mechanism. The derivations are provided for an uncoded system as well as a coded system with a given bit error rate. The proposed packetization policy provides an optimal packetization interval that minimizes the end-to-end delay for a given channel with certain bit error probability. This algorithm can also be used for near-optimal bundling of input symbols for dynamic channel conditions provided that the channel condition varies slowly over time with respect to symbol arrival rate. This algorithm complements the current network-based delay-optimal routing and scheduling algorithms in order to further reduce the end-to-end delivery time. Moreover, the proposed method is employed to solve the problem of energy efficiency maximization under an average delay constraint by recasting it as a convex optimization problem.

Goodput maximization in opportunistic spectrum access networks under constraints on the inter-packet transmission waiting time

We consider the problem of selecting the packet size, the Forward Error Correction (FEC) coding rate, and the duration of the spectrum sensing interval, which maximize the communication goodput (payload bits correctly received per unit time) of the Secondary Users (SUs) of a cognitive radio network. We start by deriving a closed form expression of the SUs achievable goodput under the assumption of Markovian primary channel use and perfect spectrum sensing. Then, we show that the optimal packet size and FEC coding rate selection change in case we impose a constraint on the maximum time SUs can wait before successfully transmitting a packet, i.e., on what we call the inter-packet transmission waiting time. Such waiting time depends on the alternating PU presence on the channel. Finally, we derive upper and lower bounds on the achievable goodput, which allow us to optimally select the packet size, the FEC coding rate, and the duration of the spectrum sensing time interval, in case of imperfect spectrum sensing. Extensive simulation results are provided that validate our findings. Specifically, we show that by adaptively and jointly selecting the system parameters as a function of received SU power and PU traffic statistics, it is possible to achieve a goodput increase in the order of 20%.

Performance improvement in DTNs by packet size optimization

In space communication environments, most studies in delay tolerant networks (DTNs) adopt experimental approaches and they have shown that the utilization efficiency of link bandwidth can be affected by changing packet sizes at the bundle layer and the convergence layer. However, the lack of theoretical work makes it difficult to find the optimal packet sizes in general scenarios. In this paper, we focus on this important issue by performing a theoretical analysis to solve the packet size optimization problems in both one-hop and multihop DTNs. As our analysis is based on the widely used DTN architecture with Bundle Protocol (BP) and Licklider Transmission Protocol (LTP), the theoretical results can be applied to any DTN scenario using this architecture. We formulate packet size optimization problems in DTNs as nonconvex optimization problems. Furthermore, a goodput enhancement algorithm (GEA) is also proposed to find the optimal packet sizes in order to maximize goodput in DTNs. We conduct numerical analysis as well as simulations to validate our theoretical analysis and study the factors that determine the optimal packet sizes for BP and LTP. Numerical results show that GEA achieves significant performance improvement compared with schemes where packet size optimization on BP and LTP is not jointly considered.

Optimal Scheduling for Wireless On-Demand Data Packet Delivery to High-Speed Trains

In this paper, we consider a cellular/infostation integrated network that supports on-demand data service delivery over a wireless link to users in a high-speed train. For the requests with different lifetimes and prices that they are willing to pay, we develop the optimal packet schedule that aims at earning the maximum revenue. To this end, we formulate the problem as an integer linear program (ILP). The problem cannot be solved efficiently by existing ILP solvers with guaranteed polynomial-time complexity in the worst case. By exploring the special structure of the formulated ILP, we propose a novel Checker algorithm and prove that this algorithm is guaranteed to find the offline optimal schedule in polynomial time. Based on the relevant insights, we further develop a class of online Checker algorithms that require only causal knowledge of service demands and wireless channel capacities. It is established that these online algorithms have a worst-case competitive ratio of 1/2, i.e., total revenue earned by them is at least half as much as the revenue earned by an offline optimal schedule that knows the complete a priori knowledge of future requests and channel conditions. Simulation results are provided to demonstrate the merit of the proposed algorithms.

Exploiting Error Estimating Codes for Packet Length Adaptation in Low-Power Wireless Networks

We propose Plena, a packet length adaptation scheme exploiting recently proposed error estimating codes (EEC) for low-power wireless networks. We carefully consider two low-power MAC protocols in modeling the energy consumption of different packet lengths. Based on the modeling and analysis, we give closed form solutions for the optimal packet length in terms of energy efficiency. EEC allows for instant estimation of the bit error rate (BER) in a partially correct packet, making it possible for predicting packet reception ratios (PRRs) at different packet lengths without the need of direct measurement in an iterative process. Fast convergence of Plena makes it suitable for mobile environments in which the channel characteristics are frequently changing. We evaluate Plena’s computation overhead based on the commonly used TelosB nodes. Results show that the computation overhead of Plena is acceptably small. We also perform extensive simulations and testbed experiments to study the performance of Plena under different configurations. Results show that Plena achieves better energy efficiency than existing works.

Optimal packet scan against malicious attacks in smart grids

With the integration of advanced computing and communication technologies, the Smart Grid is expected to greatly enhance efficiency and reliability of future power systems with renewable energy resources, as well as distributed intelligence and demand response. Along with the salient features of the Smart Grid, cyber security emerges to be a critical issue because millions of electronic devices are inter-connected via communication networks throughout critical power facilities, which has an immediate impact on reliability of such a widespread infrastructure. In this paper, we discuss the packet based attacks and study the Optimal Inspection Points (OIP) problem, which asks us to find a subset of nodes in a given network to perform the Deep Packet Inspection so as to maximize the number of scanned packets while satisfying the delay constraints. This problem finds many applications for malicious attack detection, especially for those cases where each single packet or the network traffic is required to be inspected. Accordingly, we prove OIP is NP-complete and provide an FPTAS in the case of single path routing. For the multiple path routings, we design an FPTAS when the routing graph takes a form of series-parallel graphs, which is commonly used to model electric networks. We also discuss the multi-scan scenario and design PIVOT algorithm to tackle the problem and evaluate the algorithms through experiments.