Overhead Analysis Research Articles

On the analysis of big data indexing execution strategies

Efficient response to search queries is very crucial for data analysts to obtain timely results from big data spanned over heterogeneous machines. Currently, a number of big-data processing frameworks are available in which search operations are performed in distributed and parallel manner. However, implementation of indexing mechanism results in noticeable reduction of overall query processing time. There is an urge to assess the feasibility and impact of indexing towards query execution performance. This paper investigates the performance of state-of-the-art clustered indexing approaches over Hadoop framework which is de facto standard for big data processing. Moreover, this study leverages a comparative analysis of non-clustered indexing overhead in terms of time and space taken by indexing process for varying volume data sets with increasing Index Hit Ratio. Furthermore, the experiments evaluate performance of search operations in terms of data access and retrieval time for queries that use indexes. We then validated the obtained results using Petri net mathematical modeling. We used multiple data sets in our experiments to manifest the impact of growing volume of data on indexing and data search and retrieval performance. The results and highlighted challenges favorably lead researchers towards improved implication of indexing mechanism in perspective of data retrieval from big data. Additionally, this study advocates selection of a non-clustered indexing solution so that optimized search performance over big data is obtained.

Collaborative framework for protection against attacks targeting BGP and edge networks

This paper presents the design and data-driven overhead analysis of PrefiSec, a distributed framework that helps collaborating organizations to effectively maintain and share network information in the fight against miscreants. PrefiSec is a novel distributed IP-prefix-based solution, which maintains information about the activities associated with IP prefixes (blocks of IP addresses) and autonomous systems (AS) and enables efficient sharing of this information between participants. Within PrefiSec, we design and evaluate simple and scalable mechanisms that help to protect against prefix/subprefix attacks and interception attacks, and enable sharing of prefix related information related to a wide range of edge-based attacks, such as spamming and scanning. We also include an evaluation of which ASes need to collaborate, to what extent the size and locality of ASes matter, and how many ASes are needed to achieve good efficiency in detecting anomalous route announcements. Public wide-area BGP-announcements, traceroutes, and simulations are used to estimate the overhead, scalability, and alert rates. Our results show that PrefiSec helps improve system security, and can scale to large systems.

Overhead Analysis of AOF Rewrite Method in Redis

Overhead Analysis of AOF Rewrite Method in Redis

Publisher's Note: Overhead analysis of universal concatenated quantum codes [Phys. Rev. A 95 , 022313 (2017)

Received 15 February 2017DOI:https://doi.org/10.1103/PhysRevA.95.029904©2017 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasQuantum computationQuantum error correctionQuantum Information

A Hybrid Approach for Efficient Privacy-Preserving Authentication in VANET

A vehicular ad hoc network (VANET) serves as an application of the intelligent transportation system that improves traffic safety as well as efficiency. Vehicles in a VANET broadcast traffic and safety-related information used by road safety applications, such as an emergency electronic brake light. The broadcast of these messages in an open-access environment makes security and privacy critical and challenging issues in the VANET. A misuse of this information may lead to a traffic accident and loss of human lives atworse and, therefore, vehicle authentication is a necessary requirement. During authentication, a vehicle’s privacy-related data, such as identity and location information, must be kept private. This paper presents an approach for privacy-preserving authentication in a VANET. Our hybrid approach combines the useful features of both the pseudonym-based approaches and the group signature-based approaches to preclude their respective drawbacks. The proposed approach neither requires a vehicle to manage a certificate revocation list, nor indulges vehicles in any group management. The proposed approach utilizes efficient and lightweight pseudonyms that are not only used for message authentication, but also serve as a trapdoor in order to provide conditional anonymity. We present various attack scenarios that show the resilience of the proposed approach against various security and privacy threats. We also provide analysis of computational and communication overhead to show the efficiency of the proposed technique. In addition, we carry out extensive simulations in order to present a detailed network performance analysis. The results show the feasibility of our proposed approach in terms of end-to-end delay and packet delivery ratio.

InnoDB 기반 DBMS에서 다중 버퍼 풀 오버헤드 분석

대규모 웹 서비스의 등장으로 데이터의 규모가 점차 증가하는 추세이다. 이러한 대규모 데이터를 효율적으로 관리하기 위해 MySQL과 MariaDB와 같은 DBMS가 주로 사용되고 있으며, 이들은 데이터 관리를 위한 스토리지 엔진으로 InnoDB를 주로 사용한다. InnoDB는 ACID를 보장할 뿐만 아니라 대규모 데이터 처리에 적합하다는 장점이 있기 때문이다. InnoDB의 경우, I/O 성능 향상을 위해 버퍼 풀을 통해 데이터와 인덱스를 캐싱하며 락 경쟁(lock contention)을 줄이기 위해 다중 버퍼 풀을 지원한다. 그러나 다중 버퍼 풀 기법은 데이터 일관성 오버헤드를 증가시킨다. 본 논문에서는 다중 버퍼 풀 기법의 오버헤드를 분석한다. 실험 결과, 다중 버퍼 풀 기법을 사용함에 따라 락 경쟁이 최대 46.3%까지 완화되었지만 디스크 I/O와 fsync 명령이 증가하면서 DBMS의 처리량이 50.6%까지 떨어지는 현상을 확인하였다.

ASA-FTL: An adaptive separation aware flash translation layer for solid state drives

• An innovative FTL approach (ASA-FTL) for identifying and separating hot/cold data at the page level based on data clustering for SSDs; • A sampling and selective caching technique to control the overhead of clustering-based hot/cold data separation approach; • A Hotness Updating Algorithm that samples and clusters data periodically to update the separation criteria and an overhead analysis of the approach; • An evaluation of the proposed approach using the FlashSim simulator with several real world workloads, showing the performance benefits of our approach compared to a current state of the art FTL; • An evaluation of the effect of the sample size and the adaptivity of the proposed ASA-FTL. The flash-memory based Solid State Drive (SSD) presents a promising storage solution for increasingly critical data-intensive applications due to its low latency (high throughput), high bandwidth, and low power consumption . Within an SSD, its Flash Translation Layer (FTL) is responsible for exposing the SSD’s flash memory storage to the computer system as a simple block device. The FTL design is one of the dominant factors determining an SSD’s lifespan and performance. To reduce the garbage collection overhead and deliver better performance, we propose a new, low-cost, adaptive separation-aware flash translation layer (ASA-FTL) that combines sampling, data clustering and selective caching of recency information to accurately identify and separate hot/cold data while incurring minimal overhead. We use sampling for light-weight identification of separation criteria, and our dedicated selective caching mechanism is designed to save the limited RAM resource in contemporary SSDs. Using simulations of ASA-FTL with both real-world and synthetic workloads, we have shown that our proposed approach reduces the garbage collection overhead by up to 28% and the overall response time by 15% compared to one of the most advanced existing FTLs. We find that the data clustering using a small sample size provides significant performance benefit while only incurring a very small computation and memory cost. In addition, our evaluation shows that ASA-FTL is able to adapt to the changes in the access pattern of workloads, which is a major advantage comparing to existing fixed data separation methods.

Overhead Analysis of Reactive Shortest Single and Multi-path Routing Mechanism with Load Balance in MANET

Overhead Analysis of Reactive Shortest Single and Multi-path Routing Mechanism with Load Balance in MANET

Provably secure biometric‐based user authentication and key agreement scheme in cloud computing

AbstractCloud computing, the conjoin of many types of computing, has made a great impact on the life of everyone. People from anywhere can access the different cloud‐based services by using the Internet. A user, who wants to access some cloud‐based service, needs to register himself/herself to an authority (service provider), and after that, he/she can use the service. To access the service, each user needs to authenticate to that particular cloud server. Several user authentication schemes for cloud computing have been presented but mostly have limitations/drawbacks as they are prone to various known attacks, such as privileged insider, user and server impersonation, and strong reply attacks, and they also have lack of functionality features. Moreover, these schemes do not provide efficient password change phase. In order to overcome these drawbacks, we propose a new provably secure biometric‐based user authentication and key agreement scheme for cloud computing. The proposed scheme overcomes the weaknesses of the existing schemes and supports extra functionality features including user anonymity and efficient password and biometric update phase for multi‐server environment. The careful formal security analysis under standard model and informal security analysis and the simulation results for formal security verification using the most acceptable AVISPA tool show that the proposed scheme is secure against various known possible attacks. The analysis of computation and communication overheads of our scheme depicts its efficiency over other related existing schemes, and thus, the proposed scheme is suitable for the cloud computing environment. Copyright © 2016 John Wiley & Sons, Ltd.

Staged Growth Codes: Intermediate Performance and Overhead Analysis

It is well known that the overhead and error performances of LT codes are primarily determined by the degrees of output symbols. This letter derives a novel relationship using the AND–OR tree analytical technique between the redundancy and release probabilities, and the degree of output symbols in LT codes. Armed with this new relationship, we propose a new class of so-called staged growth codes (SGCs), which can provide the intermediate performance. We investigate the asymptotic performance of the proposed SGCs. In comparison with the conventional growth codes, the SGCs need less feedback messages and the overhead is nearly the same as LT codes when the number of blocks is not too much. Observed from the numerical results, an additional attractive feature of the SGCs in comparison with the growth codes is that the SGCs can provide the often desirable unequal error protection property.

Computation and Communication Evaluation of an Authentication Mechanism for Time-Triggered Networked Control Systems.

In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems.

Feedback Overhead Analysis for Base Station Cooperative Transmission

In this paper, we analyze the feedback overhead of channel direction information for downlink coherent base station (BS) cooperative transmission. The per-cell codebooks are considered, which are of practice importance. Instead of analyzing the required number of bits for feedback to keep a constant rate loss, we analyze the required overhead to ensure a target average signal-to-interference-plus-noise ratio (SINR) of each user. To this end, we formulate an optimization problem of bit allocation among the codebooks for local and cross channels that minimizes the total number of bits under the constraint of the average SINR, and find the explicit expression of the solution. We proceed to study the impact of various system parameters and channel features on the overall feedback overhead. Analytical and simulation results reveal that the overhead scales linearly with the overall number of transmit antennas, but decreases with the grow of the cell-edge signal-to-noise ratio. Moreover, the overhead can be significantly reduced by exploiting the diverse performance requirements of the users and the heterogeneous channel features through allocating the number of bits for feedback among multiple users and multiple per-cell links. This provides useful insight for the feedback strategy design of BS cooperation systems.

Robust resource allocations through performance modeling with stochastic process algebra

SummaryParallel and distributed computing has led to a proliferation in solving computationally intensive mathematical, science, or engineering problems. However, such computational environments are often prone to unpredictable variations due to problem, algorithm, and system characteristics. Therefore, a robustness study of resource allocations and application scheduling is required to guarantee a desired level of performance. Given an initial workload, a mapping of applications to resources is considered to be robust if it optimizes the execution performance and guarantees a desired level of performance in the presence of unpredictable perturbations at runtime. In this research work, a stochastic process algebra, performance evaluation process algebra, is used for obtaining performance of various resource allocations via a numerical analysis of performance modeling of the parallel execution of applications on parallel computing resources. Further, a robustness analysis of various allocations is performed for finding a robust mapping from a set of initial mapping schemes. The numerical results obtained from this performance modeling of resource allocations have been validated by the simulation results of earlier research, which are available from the existing literature, thus underscoring the significance of using stochastic process algebra models in providing a cost‐effective and low overhead analysis of robustness. Copyright © 2016 John Wiley & Sons, Ltd.

A limited feedback scheme for massive MIMO systems based on principal component analysis

Massive multiple-input multiple-output (MIMO) is becoming a key technology for future 5G cellular networks. Channel feedback for massive MIMO is challenging due to the substantially increased dimension of the channel matrix. This motivates us to explore a novel feedback reduction scheme based on the theory of principal component analysis (PCA). The proposed PCA-based feedback scheme exploits the spatial correlation characteristics of the massive MIMO channel models, since the transmit antennas are deployed compactly at the base station (BS). In the proposed scheme, the mobile station (MS) generates a compression matrix by operating PCA on the channel state information (CSI) over a long-term period, and utilizes the compression matrix to compress the spatially correlated high-dimensional CSI into a low-dimensional representation. Then, the compressed low-dimensional CSI is fed back to the BS in a short-term period. In order to recover the high-dimensional CSI at the BS, the compression matrix is refreshed and fed back from MS to BS at every long-term period. The information distortion of the proposed scheme is also investigated and a closed-form expression for an upper bound to the normalized information distortion is derived. The overhead analysis and numerical results show that the proposed scheme can offer a worthwhile tradeoff between the system capacity performance and implementation complexity including the feedback overhead and codebook search complexity.

NBTI-Aware Design of Integrated Circuits: A Hardware-Based Approach for Increasing Circuits’ Life Time

Advances in CMOS technology have made possible the increase of integrated circuit's density, which impacts directly on the circuit's performance. However, technology scaling poses some reliability concerns that directly affect the circuit's lifetime. One of the most important issues in nanoscale circuits is related to the time-dependent variation caused by Negative Bias Temperature Instability (NBTI). This phenomenon increases the threshold voltage of pMOS transistors, which introduces delay along the integrated circuits' paths, eventually causing functional failures. In this paper, a hardware-based technique able to increase the lifetime of Integrated Circuits (ICs) is proposed. In more detail, the technique is based on an on-chip sensor able to monitor IC's aging and to adjust its power supply voltage in order to minimize NBTI effects and increase the circuit's lifetime. Experimental results obtained throughout simulations demonstrate the technique's efficiency, since the circuit's lifetime has been increased by 150 %. Finally, the analysis of the main overheads introduced as well as the impact related to process variation renders the evaluation of the proposed approach possible.

Energy-Efficient and Low Signaling Overhead Cooperative Relaying With Proactive Relay Subset Selection

Energy efficient wireless communications have recently received much attention, due to the ever-increasing energy consumption of wireless communication systems. In this paper, we propose a new energy-efficient cooperative relaying scheme that selects a subset of relays before data transmission, through proactive participation of available relays using their local timers. We perform theoretical analysis of energy efficiency under maximum transmission power constraint, using practical data packet length, and taking account of the overhead for obtaining channel state information, relay selection, and cooperative beamforming. We provide the expression of average energy efficiency for the proposed scheme, and identify the optimal number and location of relays that maximize energy efficiency of the system. A closed-form approximate expression for the optimal position of relays is derived. We also perform overhead analysis for the proposed scheme and study the impact of data packet lengths on energy efficiency. The analytical and simulation results reveal that the proposed scheme exhibits significantly higher energy efficiency as compared to direct transmission, best relay selection, all relay selection, and a state-of-the-art existing cooperative relaying scheme. Moreover, the proposed scheme reduces the signaling overhead and achieves higher energy savings for larger data packets.

A Hierarchical Privacy Preserving Pseudonymous Authentication Protocol for VANET

Vehicular ad hoc network (VANET) is a technology that enables smart vehicles to communicate with each other and form a mobile network. VANET facilitates users with improved traffic efficiency and safety. Authenticated communication becomes one of the prime requirements of VANET. However, authentication may reveal a user's personal information such as identity or location, and therefore, the privacy of an honest user must be protected. This paper proposes an efficient and practical pseudonymous authentication protocol with conditional privacy preservation. Our protocol proposes a hierarchy of pseudonyms based on the time period of their usage. We propose the idea of primary pseudonyms with relatively longer time periods that are used to communicate with semi-trusted authorities and secondary pseudonyms with a smaller life time that are used to communicate with other vehicles. Most of the current pseudonym-based approaches are based on certificate revocation list (CRL) that causes significant communication and storage overhead or group-based approaches that are computationally expensive and suffer from group-management issues. These schemes also suffer from trust issues related to certification authority. Our protocol only expects an honest-but-curious behavior from otherwise fully trusted authorities. Our proposed protocol protects a user's privacy until the user honestly follows the protocol. In case of a malicious activity, the true identity of the user is revealed to the appropriate authorities. Our protocol does not require maintaining a CRL and the inherent mechanism assures the receiver that the message and corresponding pseudonym are safe and authentic. We thoroughly examined our protocol to show its resilience against various attacks and provide computational as well as communicational overhead analysis to show its efficiency and robustness. Furthermore, we simulated our protocol in order to analyze the network performance and the results show the feasibility of our proposed protocol in terms of end-to-end delay and packet delivery ratio.

Advantages of vertically adaptive coordinates in numerical models of stratified shelf seas

Shelf seas such as the North Sea and the Baltic Sea are characterised by spatially and temporally varying stratification that is highly relevant for their physical dynamics and the evolution of their ecosystems. Stratification may vary from unstably stratified (e.g., due to convective surface cooling) to strongly stratified with density jumps of up to 10 kg/m3 per m (e.g., in overflows into the Baltic Sea). Stratification has a direct impact on vertical turbulent transports (e.g., of nutrients) and influences the entrainment rate of ambient water into dense bottom currents which in turn determine the stratification of and oxygen supply to, e.g., the central Baltic Sea. Moreover, the suppression of the vertical diffusivity at the summer thermocline is one of the limiting factors for the vertical exchange of nutrients in the North Sea. Due to limitations of computational resources and since the locations of such density jumps (either by salinity or temperature) are predicted by the model simulation itself, predefined vertical coordinates cannot always reliably resolve these features. Thus, all shelf sea models with a predefined vertical coordinate distribution are inherently subject to under-resolution of the density structure.To solve this problem, Burchard and Beckers (2004) and Hofmeister et al. (2010) developed the concept of vertically adaptive coordinates for ocean models, where zooming of vertical coordinates at locations of strong stratification (and shear) is imposed. This is achieved by solving a diffusion equation for the position of the coordinates (with the diffusivity being proportional to the stratification or shear frequencies). We will show for a coupled model system of the North Sea and the Baltic Sea (resolution ∼ 1.8 km) how numerical mixing is substantially reduced and model results become significantly more realistic when vertically adaptive coordinates are applied. We additionally demonstrate that vertically adaptive coordinates perform well in simulating the two dynamically different regions North Sea and Baltic Sea with a single parameter set.An analysis of the computational overhead of the adaptive coordinates indicates an increase of 5–8% in runtime. This is still less expensive than adding more sigma-layers to reduce spurious numerical mixing.

Overhead Analysis and Evaluation of Approaches to Host-Based Bot Detection

Host-based bot detection approaches discover malicious bot processes by signature comparison or behavior analysis. Existing approaches have low performance which has become a bottleneck blocking its wider deployment. Among the impact factors of performance, overhead is a crucial one. Many host-based bot detection approaches with high detection accuracy are not used practically because of their high overheads. For the development of host-based bot detection, unveiling the factors affecting the overhead is very significant. First, this paper classifies the typical approaches of host-based bot detection proposed in recent years by several metrics, information sources, interception mechanisms on host, intercepted system calls, trigger mechanisms, and correlation engine. Second, based on our analyses of aims and implementations of detection approaches, we identify three major factors affecting the overhead of approaches, namely, interception mechanism on host, type, and number of system calls intercepted and correlation engine. Third, we evaluate the influence of these factors via various experiments on real systems. Finally, based on the experiments, we propose several suggestions which are able to significantly decrease the overhead of host-based bot detection approaches.

Cache-aware compositional analysis of real-time multicore virtualization platforms

Multicore processors are becoming ubiquitous, and it is becoming increasingly common to run multiple real-time systems on a shared multicore platform. While this trend helps to reduce cost and to increase performance, it also makes it more challenging to achieve timing guarantees and functional isolation. One approach to achieving functional isolation is to use virtualization. However, virtualization also introduces many challenges to the multicore timing analysis; for instance, the overhead due to cache misses becomes harder to predict, since it depends not only on the direct interference between tasks but also on the indirect interference between virtual processors and the tasks executing on them. In this paper, we present a cache-aware compositional analysis technique that can be used to ensure timing guarantees of components scheduled on a multicore virtualization platform. Our technique improves on previous multicore compositional analyses by accounting for the cache-related overhead in the components' interfaces, and it addresses the new virtualization-specific challenges in the overhead analysis. To demonstrate the utility of our technique, we report results from an extensive evaluation based on randomly generated workloads.