Decrease In Throughput Research Articles

Lifetime Estimation and Measurement for Wireless Ad Hoc Networks

Mobile ad-hoc networks (MANET) is a popular choice for “wireless communication network” due to ease of deployment. Nodes in MANET are battery operated, movable, and compact. They can sense, manipulate and communicate data wirelessly. Limited battery power of the nodes is one of the major constraints of MANET. This paper proposes a network lifetime model that considers residual energy and actual discharge rate of the battery along with the energy consumption in different modes like transmit, receive, sleep, idle, active and processing while calculating the lifetime. A circuit implementation of node with Arduino Mega 2560, ZigBee transceiver, 2100 mAh NiMH rechargeable battery was done to compare lifetime with conventional dynamic source routing (DSR) and modified Least Max Dynamic Source Routing (LMDSR) algorithms. The DSR algorithm always selects the shortest path between source and destination nodes. But the LMDSR algorithm also considers the residual battery levels of the nodes to avoid overuse of the node(s) with low battery. This will prevent the early exhaustion of node(s) which may be the reason for reduced network lifetime. The result analysis shows that the implementation of LMDSR algorithm improves the network lifetime on an average by 31% and reduces the energy consumption by 21% with a slight decrease in throughput.

Designing Efficient Sinkhole Attack Detection Mechanism in Edge-Based IoT Deployment.

The sinkhole attack in an edge-based Internet of Things (IoT) environment (EIoT) can devastate and ruin the whole functioning of the communication. The sinkhole attacker nodes (s) have some properties (for example, they first attract the other normal nodes for the shortest path to the destination and when normal nodes initiate the process of sending their packets through that path (i.e., via ), the attacker nodes start disrupting the traffic flow of the network). In the presence of s, the destination (for example, sink node i.e., gateway/base station) does not receive the required information or it may receive partial or modified information. This results in reduction of the network performance and degradation in efficiency and reliability of the communication. In the presence of such an attack, the throughput decreases, end-to-end delay increases and packet delivery ratio decreases. Moreover, it may harm other network performance parameters. Hence, it becomes extremely essential to provide an effective and competent scheme to mitigate this attack in EIoT. In this paper, an intrusion detection scheme to protect EIoT environment against sinkhole attack is proposed, which is named as SAD-EIoT. In SAD-EIoT, the resource rich edge nodes (edge servers) perform the detection of different types of sinkhole attacker nodes with the help of exchanging messages. The practical demonstration of SAD-EIoT is also provided using the well known NS2 simulator to compute the various performance parameters. Additionally, the security analysis of SAD-EIoT is conducted to prove its resiliency against various types of s. SAD-EIoT achieves around detection rate and false positive rate, which are considerably better than other related existing schemes. Apart from those, SAD-EIoT is proficient with respect to computation and communication costs. Eventually, SAD-EIoT will be a suitable match for those applications which can be used in critical and sensitive operations (for example, surveillance, security and monitoring systems).

An analytical model for IEEE 802.11 with non-IEEE 802.11 interfering source

The MAC layer of the IEEE 802.11 standard deploys a CSMA/CA protocol to regulate the access to the shared medium. Not only other IEEE 802.11 stations but also non-IEEE 802.11 devices can be a source of interference, causing collisions and, therefore, re-transmissions, leading to an increased packet latency and a decrease of throughput. As in general, the non-IEEE 802.11 devices do not employ the IEEE8 802.11 CSMA/CA protocol (in particular carrier sensing and the behavior when the medium is sensed busy), the impact of the interference they cause may lead to vital performance degradation of the IEEE 802.11 network. This impact of non-IEEE 802.11 interfering sources on the network performance has not been accurately modeled yet in literature. In this paper, we first characterize a non-IEEE 802.11 interfering source by employing an on-off process. Then we propose, based on earlier results from Bianchi, an analytical model to predict latency and throughput in a saturated as well as an unsaturated network, considering that an interfering source is present. The model utilizes a Markov chain to correctly characterize the behavior of the back-off algorithm of a tagged station in the presence of an interfering source, as well as a Quasi Birth-Death (QBD) process to model the station’s packet queue behavior. We show that we can accurately estimate the impact of non-IEEE 802.11 inference on IEEE 802.11 performance. The model is validated through a comparison with measurements in a real IEEE 802.11 network as well as with an ns3-simulation, whereby a very good agreement is achieved (a difference less than 2%).

Group-Based Uplink OFDMA Random Access Algorithm for Next-Generation WLANs

The traditional wireless local area network(WLAN) standard, IEEE 802.11, adopts carrier sense multiple access/collision avoidance(CSMA/CA) mechanism to allow a single user to compete for channel access. The upcoming WLAN standard, IEEE 802.11ax, combines orthogonal frequency division multiple access(OFDMA) technology with random access, and use Uplink OFDMA Random Access(UORA) technology as uplink random access. Therefore, UORA which allow multiple users to access channel at the same time can improve the utilization of network resources. Although UORA technology in IEEE 802.11ax has the advantage of low signaling overhead, when the number of users of network is large, the increase of random access collisions will lead to the decrease of network throughput. Therefore, we propose a group-based UORA method. As a central scheduling node, Access Point(AP) divide Stations(STAs) and resources to groups and sets different GroupID for different groups. STAs can only access resources with the same GroupID randomly. The validity of group-based UORA method is verified by mathematical model analysis and simulation. The network throughput of our group-based UORA is higher than that of the original UORA in IEEE 802.11ax, so it has great practical significance.

A Constant Time Complexity Spam Detection Algorithm for Boosting Throughput on Rule-Based Filtering Systems

Along with the barbarous growth of spams, anti-spam technologies including rule-based approaches and machine-learning thrive rapidly as well. In antispam industry, the rule-based systems (RBS) becomes the most prominent methods for fighting spam due to its capability to enrich and update rules remotely. However, the antispam filtering throughput is always a great challenge of RBS. Especially, the explosively spreading of obfuscated words leads to frequent rule update and extensive rule vocabulary expansion. These incremental obfuscated words make the filtering speed slow down and the throughput decrease. This paper addresses the challenging throughput issue and proposes a constant time complexity rule-based spam detection algorithm. The algorithm has a constant processing speed, which is independent of rule and its vocabulary size. A new special data structure, namely, Hash Forest, and a rule encoding method are developed to make constant time complexity possible. Instead of traversing each spam term in rules, the proposed algorithm manages to detect spam terms by checking a very small portion of all terms. The experiment results show effectiveness of proposed algorithm.

Using 5G Network Slicing and Non-Orthogonal Multiple Access to Transmit Medical Data in a Mobile Hospital System

In this work, we propose a novel approach combining 5G network slicing and non-orthogonal multiple access (NOMA) to transmit medical data in a mobile hospital system. We consider both the uplink and downlink of a 5G cellular network with an ambulance bus located at a remote site for data transmission in the uplink scenario and a hospital unit as the receiving site in the downlink scenario. We propose and model a NOMA slicing system where the medical data are categorized and assigned to two different slices based on 5G services. That is, 4K video from patients is assigned to an enhanced mobile broadband (eMBB) NOMA slice in both uplink and downlink, and all other medical data are assigned to an ultra-reliable and low latency communication (uRLLC) NOMA slice also in both uplink and downlink. Based on the system model and principles of NOMA, we formulate and use a joint power allocation optimization technique under users' minimum rate requirements and transmission power constraints, and successive interference cancellation (SIC) to maximize the medical data throughput as well as the system sum-throughput in each slice in both uplink and downlink. Our results show that, with the optimal power allocation technique, high throughput can be achieved for the 4K video and other medical data in the eMBB NOMA slice and uRLLC NOMA slice, respectively, but other users transmitting and receiving ordinary data in the slices will see their throughput decrease. Hence, in the interest of fairness for all users, we use truncated channel inversion power allocation in the downlink to prevent the decrease of the throughput of those users regardless of their channel conditions.

Filter Cone Spray Ionization Coupled to a Portable MS System: Application to On-Site Forensic Evidence and Environmental Sample Analysis.

The complexity of field-borne sample matrices and the instrumental constraints of portable mass spectrometers (MS) often necessitate that preparative steps are added prior to ambient MS methods when operated on-site, but the corresponding decrease in throughput and experimental simplicity can make field operation impractical. To this end, we report a modified ambient MS method, filter cone spray ionization (FCSI), specifically designed for simple, yet robust, processing of bulk forensic evidence and environmental samples using a fieldable MS system. This paper-crafted source utilizes low-cost laboratory consumables to produce a conical structure that serves as a disposable, spray-based ionization source. Integrated extraction and filtration capabilities mitigate sample heterogeneity and carryover concerns and expedite sample processing, as characterized through the analysis of a variety of authentic forensic evidence types (e.g., abused pharma tablets, counterfeit/adulterated tablets, crystal-based drugs, synthetic marijuana, toxicological specimens) and contaminated soil samples. The data presented herein suggests that the FCSI-MS design could prove robust to the rigors of field-borne, bulk sample screening, overcoming the inefficiencies of other ambient MS methods for these sample classes. Novel applications of FCSI-MS are also examined, such as the coupling to trace evidence vacuum filtration media.

Flexible low-latency metro-access converged network architecture based on optical time slice switching

The “pay-as-you-grow” cloud computing model has become popular for today’s enterprises. Cloud computing not only frees end users from complex operations, but also allows higher resource utilization, lower investment, and increased energy efficiency. However, with some emerging technologies, cloud computing is unable to meet the required latency level, especially for delay-sensitive services such as 5G communications, live streaming, and online gaming. In this context, edge computing is regarded as a promising technology that can provide low-latency connections in the near future. Unlike cloud computing, which provides service in a centralized mode, edge computing deploys micro data centers (MDCs) at the edge of the network to provide rapid-response service. However, due to the limited computing and storage capacity of a single MDC, a user may not be able to access the resources from the closest MDC during peak traffic periods. Under such circumstances, the user is served through another MDC or a remote cloud data center. The data are processed in an optical line terminal and then transmitted via the metro network, which significantly increases the latency. In this study, we introduce a flexible low-latency metro-access converged network architecture based on optical time slice switching (OTSS) to address the latency problem. By leveraging the transparent connections of the OTSS in this novel architecture, data can be transmitted through the MDCs without requiring extra processing time. The simulation results demonstrate that our proposed architecture can provide lower-latency connections under a range of conditions, with a negligible decrease in network throughput, compared with an existing representative architecture. Additionally, we conducted experiments to validate the feasibility of our approach.

A Prioritized Load Aware Weighted Round Robin (PLAWRR) algorithm in Broadband Wireless Networks

Broadband Wireless networks (BWNs) provide a reliable internet access for the delivery of high-speed multimedia applications. The BWNs such as WiMAX provides quality of service (QoS) support for heterogeneous service classes with diverse QoS requirements. Scheduling algorithm is one of the mechanisms used to assure QoS. The existing scheduling algorithm uses a priority value to prioritize traffics according to varying traffic conditions. However, it wastes network resources due to failure to consider channel conditions; thus, lead to increase in delay and packet loss as well as decrease in throughput. In this paper, a prioritized load aware weighted round robin (PLAWRR) algorithm is proposed to improve resource utilization. The PLAWRR algorithm employs a modified value priority according to not only traffic load but also channel condition and throughput history for traffics prioritization. It also introduces a new dynamic weight according to the prioritization value. The performance of the proposed algorithm is evaluated using simulations. The results show that the proposed PLAWRR achieves superior performance compared to the existing algorithm in terms of delay and packet loss as well as increase in throughput.

StealthDB: a Scalable Encrypted Database with Full SQL Query Support

Abstract Encrypted database systems provide a great method for protecting sensitive data in untrusted infrastructures. These systems are built using either special-purpose cryptographic algorithms that support operations over encrypted data, or by leveraging trusted computing co-processors. Strong cryptographic algorithms (e.g., public-key encryptions, garbled circuits) usually result in high performance overheads, while weaker algorithms (e.g., order-preserving encryption) result in large leakage profiles. On the other hand, some encrypted database systems (e.g., Cipherbase, TrustedDB) leverage non-standard trusted computing devices, and are designed to work around the architectural limitations of the specific devices used. In this work we build StealthDB – an encrypted database system from Intel SGX. Our system can run on any newer generation Intel CPU. StealthDB has a very small trusted computing base, scales to large transactional workloads, requires minor DBMS changes, and provides a relatively strong security guarantees at steady state and during query execution. Our prototype on top of Postgres supports the full TPC-C benchmark with a 30% decrease in the average throughput over an unmodified version of Postgres operating on a 2GB unencrypted dataset.

Cellular Connectivity for UAVs: Network Modeling, Performance Analysis, and Design Guidelines

The growing use of aerial user equipments (UEs) in various applications requires ubiquitous and reliable connectivity for safe control and data exchange between these devices and ground stations. Key questions that need to be addressed when planning the deployment of aerial UEs are whether the cellular network is a suitable candidate for enabling such connectivity, and how the inclusion of aerial UEs might impact the overall network efficiency. This paper provides an in-depth analysis of user and network level performance of a cellular network that serves both unmanned aerial vehicles (UAVs) and ground users in the downlink. Our results show that the favorable propagation conditions that UAVs enjoy due to their height often backfire on them, as the increased co-channel interference received from neighboring ground BSs is not compensated by the improved signal strength. When compared with a ground user in an urban area, our analysis shows that a UAV flying at 100 meters can experience a throughput decrease of a factor 10 and a coverage drop from 76% to 30%. Motivated by these findings, we develop UAV and network based solutions to enable an adequate integration of UAVs into cellular networks. In particular, we show that an optimal tilting of the UAV antenna can increase their coverage and throughput from 23% to 89% and from 3.5 b/s/Hz to 5.8 b/s/Hz, respectively, outperforming ground UEs. Furthermore, our findings reveal that depending on UAV altitude, the aerial user performance can scale with respect to the network density better than that of a ground user. Finally, our results show that network densification and the use of micro cells limit UAV performance. While UAV usage has the potential to increase area spectral efficiency (ASE) of cellular networks with moderate number of cells, they might hamper the development of future ultra dense networks.

The effect of new compounds in stabilizing downstream monoclonal antibody (mAb) process intermediates.

Determining the stability of downstream process (DSP) intermediates is an extremely important parameter used to maintain product quality attributes within their acceptance ranges. The IgG4 monoclonal antibody studied (mAb1) showed aggregation under acidic conditions, inhibiting the use of low pH treatment to inactivate endogenous retroviruses, and poor virus filtration performance. Both manufacturing steps are included in mAb DSP for viral clearance. The impact of several new compounds on the aggregation and stabilization of mAb1 in process intermediate pools encountered during these critical DSP steps was investigated. Results showed that, in the presence of a protein stabilizer at pH 3.2, 27% less aggregation was observed compared to controls, during the low pH treatment for viral inactivation. The impact of a novel protein stabilizer on virus filter throughput during mAb1 filtration was compared to L-arginine using an innovative high-throughput automation technique. Compared to control experiments without additives, conditions were found where a 70% increase in filter volumetric throughput was achieved in the presence of the novel stabilizer, and a 56% decrease in volumetric throughput observed with L-arginine. These findings present the possibility of using these novel compounds to stabilize proteins during DSP and permitting the use of platform DSP elements such as low pH treatment and high-throughput virus filtration to challenging and unstable proteins.

Performance Analysis of AODV under Black Hole Attack

In this paper, we represent the effect of Black Hole attack in AODV routing protocol in MANET is analyzed. We also compare the network performance of standard AODV against Black Hole attack on AODV routing protocol. Simulation is carried out using NS-2.35. It depicts that PDR percentage and Average Throughput decrease and End to End Delay (EED) increases due to the presence of malicious nodes in the Mobile Ad-Hoc Network.

Meningkatkan Efisiensi Rute Pada Protokol Routing AOMDV Menggunakan Metode PA-SHORT di Jaringan MANET

Mobile Ad-Hoc Network (MANET) is a development of the Ad-Hoc Network, where the nodes of this network have dynamic mobility. There are several types of routing protocols in MANET, one of which is AOMDV. Route discovery on the AOMDV routing protocol is done by calculating the distance based on the number of hops. If the number of hops increased, it may cause a considerable delay and a decrease in throughput. This study compares the performance of the AOMDV routing protocol with the Path Aware-AOMDV (PA-AOMDV) routing protocol. PA-AOMDV routing protocol is obtained through modifications to the performance of the AOMDV protocol with the Path Aware SHORT algorithm. The Path Aware SHORT algorithm is a method to reduce the number of hops. SHORT improves routing optimization by monitoring routes and optimizing these routes that have better paths. The performance of both protocols will be seen based on four parameters, namely throughput, average end-to-end delay, packet delivery ratio, and routing overhead. Result shows that the throughput increased for 50 nodes is 61,84% and for 100 nodes is 45,2%, average end-to-end delay decreased for 50 nodes is 0,066% and for 100 nodes 0,12%, packet delivery ratio increased for 50 nodes is 60,87% and for 100 nodes 82,02%, and routing overhead decreased for 50 nodes is 67,07% and 100 nodes 45,36%.

Dynamic Voltage and Frequency Scaling in NoCs with Supervised and Reinforcement Learning Techniques

Network-on-Chips (NoCs) are the de facto choice for designing the interconnect fabric in multicore chips due to their regularity, efficiency, simplicity, and scalability. However, NoC suffers from excessive static power and dynamic energy due to transistor leakage current and data movement between the cores and caches. Power consumption issues are only exacerbated by ever decreasing technology sizes. Dynamic Voltage and Frequency Scaling (DVFS) is one technique that seeks to reduce dynamic energy; however this often occurs at the expense of performance. In this paper, we propose LEAD Learning-enabled Energy-Aware Dynamic voltage/frequency scaling for multicore architectures using both supervised learning and reinforcement learning approaches. LEAD groups the router and its outgoing links into the same V/F domain and implements proactive DVFS mode management strategies that rely on offline trained machine learning models in order to provide optimal V/F mode selection between different voltage/frequency pairs. We present three supervised learning versions of LEAD that are based on buffer utilization, change in buffer utilization and change in energy/throughput, which allow proactive mode selection based on accurate prediction of future network parameters. We then describe a reinforcement learning approach to LEAD that optimizes the DVFS mode selection directly, obviating the need for label and threshold engineering. Simulation results using PARSEC and Splash-2 benchmarks on a 4 × 4 concentrated mesh architecture show that by using supervised learning LEAD can achieve an average dynamic energy savings of 15.4 percent for a loss in throughput of 0.8 percent with no significant impact on latency. When reinforcement learning is used, LEAD increases average dynamic energy savings to 20.3 percent at the cost of a 1.5 percent decrease in throughput and a 1.7 percent increase in latency. Overall, the more flexible reinforcement learning approach enables learning an optimal behavior for a wider range of load environments under any desired energy versus throughput tradeoff.

Relationship among operational parameters, ore characteristics, and product shape properties in an industrial SAG mill

A detailed test work was carried out with an industrial semi-autogenous (SAG) mill in a copper plant in close and open circuits to specify the effects of ore characteristics and operational parameters on mill performance. In addition, the shape of mill product particles was studied to monitor breakage events as a function of ore strength. For this purpose, the strength properties of the SAG mill feed and product were specified by different techniques, including the point load index, impact breakage parameters (A × b), abrasion index (ta), and Bond ball mill work index (Wi). Experimental studies showed that an increase in ore hardness is linked with an increase in point load index and Bond work index and a decline in impact breakage parameter (A × b). Hard ore grinding resulted in finer products, compared to the soft ore milling. The softer ore is ground chiefly via the impact breakage whereas the stronger ore is subjected to abrasion and attrition events where the media impact could not sufficiently break the stronger particles. The main reason for the decrease of circuit throughput was changes in breakage mechanisms. The results displayed that the highest aspect ratio and the lowest circularity of mill product are achieved by soft ore milling. As ore strength changes, differences in shape can be attributed to the different breakage mechanisms operated in the mill. In addition, the particle shape characteristics provide a convenient way to quantify changes in SAG mill as a function of the ore properties and the kind of breakage action used.

Comparing nonredundant masking and filled-aperture kernel phase for exoplanet detection and characterization

The limitations of adaptive optics and coronagraph performance make exoplanet detection close to {\lambda}/D extremely difficult with conventional imaging methods. The technique of non-redundant masking (NRM), which turns a filled aperture into an interferometric array, has pushed the planet detection parameter space to within {\lambda}/D. For high Strehl, the related filled-aperture kernel phase technique can achieve resolution comparable to NRM, without the associated dramatic decrease in throughput. We present non-redundant masking and kernel phase contrast curves generated for ground- and space-based instruments. We use both real and simulated observations to assess the performance of each technique, and discuss their capabilities for different exoplanet science goals such as broadband detection and spectral characterization.

Modeling and Performance Analysis of the Main MAC and PHY Features of the 802.11ac Standard: A-MPDU Aggregation vs Spatial Multiplexing

The Very High Throughput (VHT) supplied by the IEEE 802.11ac standard is the outcome of several amendments incorporated at its both Medium Access Control (MAC) and PHYsical (PHY) layers. In particular, the Aggregate-MAC Protocol Data Unit (A-MPDU) frame aggregation allows, at the MAC level, increasing the amount of data to be transmitted and the spatial multiplexing technique serves at the PHY level to accelerate the rate at which such data are forwarded. Therefore, the goals we are seeking to achieve in this paper are, on one hand, to demonstrate that A-MPDU aggregation and spatial multiplexing may, respectively, lead to a decrease in throughput and an increase in overhead, and on the other hand, to highlight that A-MPDU aggregation and spatial multiplexing have mutual needs that could mutually satisfy operational challenges. For this purpose, we model the 802.11ac station enabling A-MPDU aggregation and spatial multiplexing, and we compute the throughput and the overhead of the 802.11ac network. After that, we run Monte Carlo simulations for validating the accuracy of the mathematical model, and we calculate 95% confidence intervals to establish credibility to the simulation results.

Throughput analysis of dynamic spectrum anti-jamming multiple-access in HF communication systems

A multiple-access networking scheme based on the new dynamic spectrum anti-jamming system is proposed in this paper. The network consists of a center node and multiple user nodes. The center node detects spectrum holes in the operation band periodically according to the user performance target. Detected spectrum holes are allocated to users who request communication. Throughput of this networking scheme is analyzed over a high-frequency (HF) interference channel. The effect of error correction coding and spectrum hole information transmission error is discussed. Throughput of this scheme and conventional frequency-hopping multiple-access (FHMA) scheme are compared. Results show that user performance increase leads to throughput decrease, which can be offset by error correction coding. If spectrum hole information transmission is in error, the throughput is not affected much as long as the bit error rate is below 10−2. Furthermore, throughput of this scheme is obviously superior to the throughput of FHMA scheme.

FEATURES OF MORPHOFUNCTIONAL REMODELLING OF RAT HEPATOCYTES AND THEIR QUANTITATIVE CHARACTERISTICS AGAINST THE GROUND OF CHRONIC ACETYLSALICYLIC ACID POISONING

According to the results of the study, it has been established that chronic acetylsalicylic acid poisoning results in severe liver disorders presented by both venous and portal blood overloaded with a reflex throughput decrease of the arterial part of the bloodstream. Prolonged venous stasis and reflex vasoconstriction of arteries lead to ischemia of the liver tissue with the development and progression of dystrophic changes in hepatocytes. With an increase in the duration of observation, there is an expansion of cell zones with signs of granular dystrophy, which pass into fields with dystrophy of hepatic cells, damage of intercellular boundaries, homogenization of cytoplasm and degradation of nuclei of hepatocytes. It was manifested quantitatively by an increase in the cross-section of hepatocytes and their nuclei with an appropriate dynamics of nuclear-cytoplasmic relations.