线程池技术在并发服务器中的应用

线程池技术能有效减少多线程环境中资源的消耗,可以提高系统的处理能力。因此现在的服务器程序中大量应用该技术,可以最大程度的利用系统的资源,消除系统因频繁创建、销毁线程而带来的系统开销。文章就利用线程池技术来解决并发服务器中客户端频繁对服务器端请求服务这一应用场景,分析了线程池的工作原理,并做了仿真测试,证明了线程池在应用中确实有比较好的效果。     

制丝线加香加料系统的问题及改进方法

针对目前卷烟企业制丝线加香、加料系统普遍存在的问题,从设备选型、控制算法进行分析,提出改进方法。     

基于AOP技术的通用线程监控平台GTMP*

提出并实现了基于AOP技术的通用线程监控平台。借助AOP的需求空间分离实现技术,使用该平台的原系统不必事先具有监控能力,该平台可以在不手动改变系统源代码的情况下通过工具自动植入系统内部,为系统注入监控功能,实现对运行线程信息的监视和对指定线程运行速度的变换,实现对整个系统运行行为的控制。     

基于混合机制的Kerberos安全性增强方案

针对Kerberos协议的弱点和安全性问题,提出了一个基于混合加密机制的Kerberos改进方案,目的是防范口令攻击和内部攻击。给应用服务器和AS服务器分配公钥和私钥,用户与服务器之间的会话密钥由DH密钥交换生成。给出了改进后的 Kerberos 协议的六个步骤,并对安全性进行分析。分析结果表明,新方案能够增强Kerberos协议的安全性,而且比公钥加密机制高效。     

一种隐藏注入模块的新方法

在信息安全领域,安全分析工具往往需要将监控模块注入到其他进程空间以实现监控功能,但恶意软件往往会通过检测自身空间是否有其他模块来逃避监控。因此,安全工具需要对注入模块加以隐藏。比较常见的隐藏方法有:断开进程的LDR_MODULE链、Hook枚举模块的函数、抹去PE头等,但这些方法都有比较大的局限性。针对这些局限性,提出了一种对注入模块进行隐藏的新方法。在注入时利用普通有模块注入方式,让恶意软件疏于防范;注入之后消除自身模块,让恶意软件无法检测到监控软件的存在。对于应用中的一些具体技术问题给出了解决方法。实验结果表明,该方法突破防御能力强,可兼容各种版本的Windows操作系统,并且隐蔽性比目前的通用方法更好。     

多线程的效率

用Java语言定义了一个线程类,并用System类中的静态方法eurrentTimeMillis()计算时间,从而比较了用不同个数的线程求数组元素和的时间.通过实验证明在LimLx、Windows 2000 Advanced Server和Windows XPProfessional系统中,在加数个数一定的条件下,并不是线程数越多,效率越高.而是要用合适的线程数.同时通过分析了在Windows XP Professional中,不同配置的计算机线程个教与加数的关系相似.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

木马隐藏技术与防范方法

为加固网络安全、防范木马攻击,结合实例研究了一种木马隐藏技术,实现了基于加载三级跳和线程守护的隐藏技术,增强了木马的隐蔽性与抗毁性,并提出了该技术相应的防范措施和清除方法。实验结果表明,融入该隐藏技术的木马程序完成了预期的隐藏功能并可以穿透最新的瑞星杀毒软件、瑞星防火墙及硬件防火墙,表明了该隐藏技术的可行性与有效性。     

Adapting application execution in CMPs using helper threads

In parallel to the changes in both the architecture domain–the move toward chip multiprocessors (CMPs)–and the application domain–the move toward increasingly data-intensive workloads–issues such as performance, energy efficiency and CPU availability are becoming increasingly critical. The CPU availability can change dynamically due to several reasons such as thermal overload, increase in transient errors, or operating system scheduling. An important question in this context is how to adapt, in a CMP, the execution of a given application to CPU availability change at runtime. Our paper studies this problem, targeting the energy-delay product (EDP) as the main metric to optimize. We first discuss that, in adapting the application execution to the varying CPU availability, one needs to consider the number of CPUs to use, the number of application threads to accommodate and the voltage/frequency levels to employ (if the CMP has this capability). We then propose to use helper threads to adapt the application execution to CPU availability change in general with the goal of minimizing the EDP. The helper thread runs parallel to the application execution threads and tries to determine the ideal number of CPUs, threads and voltage/frequency levels to employ at any given point in execution. We illustrate this idea using four applications (Fast Fourier Transform, MultiGrid, LU decomposition and Conjugate Gradient) under different execution scenarios. The results collected through our experiments are very promising and indicate that significant EDP reductions are possible using helper threads. For example, we achieved up to 66.3%, 83.3%, 91.2%, and 94.2% savings in EDP when adjusting all the parameters properly in applications FFT, MG, LU, and CG, respectively. We also discuss how our approach can be extended to address multi-programmed workloads.