25 research outputs found
Cooperative Resource Management in a IaaS
International audienceVirtualized IaaS generally rely on a server consolidation system to pack virtual machines (VMs) on as few servers as possible, for energy saving. However, two situations are not taken into account, and could enhance consolidation. First, since the managed VMs can be of various sizes (small, medium, large, etc.), VMs packing can be obstructed when sizes don't fit available spaces on servers. Therefore, we would need to "split" such VMs. Second, two VMs which host replicas of the same application server (for scalability) could be "fusion Ned" when they are located on the same physical server, in order to reduce virtualization overhead and VMs memory footprint. Split and fusion operations lead to the management of elastic VMs and requires cooperation between the application level and the provider level, as they impact management at both levels. In this paper, we propose a IaaS resource management system which implements elastic VMs based on split/fusion operations and cooperative management. We show its benefit with a set of experiments
Tailoring Micro-solar Systems to Heterogeneous Wireless Sensor Networks
Energetic needs of wireless sensor networks (WSNs) have been thoroughly studied. Among the most important results, clustering protocols are able to reduce significantly energy consumption in these networks. In the last few years though, focus has also been put on energy harvesting for WSNs. With energy harvesting researchers aim to reach energy neutrality, which means the network only runs on harvested energy. Many papers propose design options for energy harvested WSN, but they only focus on ad-hoc solutions, homogeneous WSNs, or pose other limitations. In this paper we propose a new approach. We study the energetic need of a heterogeneous WSN clustered with a known algorithm (REECHD) through simulation, in order to calculate the minimum and ideal energy to harvest for a given network. Given that, we design an appropriate micro-solar power system to achieve energy neutrality
Performance analysis of WMN-GA simulation system for different WMN architectures considering OLSR
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Wireless Mesh Networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-GA system which is based on Genetic Algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of two different distributions of mesh clients for two WMN architectures considering throughput, delay and energy metrics. For simulations, we used ns-3 and Optimized Link State Routing (OLSR). We compare the performance for normal and uniform distributions of mesh clients by sending multiple Constant Bit Rate (CBR) flows in the network. The simulation results show that for both distributions, the throughput of Hybrid WMN is higher than I/B WMN architecture. The delay of Hybrid WMN is a lower compared with I/B WMN. The delay for Hybrid WMN is almost the same for both distributions. However for I/B WMN, the delay is lower for Uniform distribution. For Normal distribution, the energy decreases sharply, because of the high density of nodes. For Uniform distribution, the remaining energy is higher compared with Normal distribution.Peer ReviewedPostprint (author's final draft
Pseudorehearsal in actor-critic agents with neural network function approximation
Catastrophic forgetting has a significant negative impact in reinforcement
learning. The purpose of this study is to investigate how pseudorehearsal can
change performance of an actor-critic agent with neural-network function
approximation. We tested agent in a pole balancing task and compared different
pseudorehearsal approaches. We have found that pseudorehearsal can assist
learning and decrease forgetting
Pseudorehearsal in actor-critic agents with neural network function approximation
Catastrophic forgetting has a significant negative impact in reinforcement
learning. The purpose of this study is to investigate how pseudorehearsal can
change performance of an actor-critic agent with neural-network function
approximation. We tested agent in a pole balancing task and compared different
pseudorehearsal approaches. We have found that pseudorehearsal can assist
learning and decrease forgetting
Symbolic verification of event–condition–action rules in intelligent environments
In this paper we show how state-of-the art SMT-based techniques for software verification can be employed in the verification of event–condition–action rules in intelligent environments. Moreover, we exploit the specific features of intelligent environments to optimise the verification process. We compare our approach with previous work in a detailed evaluation section, showing how it improves both performance and expressivity of the language for event–condition–action rules
Symbolic verification of event–condition–action rules in intelligent environments
In this paper we show how state-of-the art SMT-based techniques for software verification can be employed in the verification of event–condition–action rules in intelligent environments. Moreover, we exploit the specific features of intelligent environments to optimise the verification process. We compare our approach with previous work in a detailed evaluation section, showing how it improves both performance and expressivity of the language for event–condition–action rules
JustSTART: How to Find an RSA Authentication Bypass on Xilinx UltraScale(+) with Fuzzing
Fuzzing is a well-established technique in the software domain to uncover
bugs and vulnerabilities. Yet, applications of fuzzing for security
vulnerabilities in hardware systems are scarce, as principal reasons are
requirements for design information access (HDL source code). Moreover,
observation of internal hardware state during runtime is typically an
ineffective information source, as its documentation is often not publicly
available. In addition, such observation during runtime is also inefficient due
to bandwidth-limited analysis interfaces (JTAG, and minimal introspection of
internal modules). In this work, we investigate fuzzing for 7-Series and
UltraScale(+) FPGA configuration engines, the control plane governing the
(secure) bitstream configuration within the FPGA. Our goal is to examine the
effectiveness of fuzzing to analyze and document the opaque inner workings of
FPGA configuration engines, with a primary emphasis on identifying security
vulnerabilities. Using only the publicly available chip and dispersed
documentation, we first design and implement ConFuzz, an advanced FPGA
configuration engine fuzzing and rapid prototyping framework. Based on our
detailed understanding of the bitstream file format, we then systematically
define 3 novel key fuzzing strategies for Xilinx configuration engines.
Moreover, our strategies are executed through mutational structure-aware
fuzzers and incorporate various novel custom-tailored, FPGA-specific
optimizations. Our evaluation reveals previously undocumented behavior within
the configuration engine, including critical findings such as system crashes
leading to unresponsive states of the FPGA. In addition, our investigations not
only lead to the rediscovery of the starbleed attack but also uncover JustSTART
(CVE-2023-20570), capable of circumventing RSA authentication for Xilinx
UltraScale(+). Note that we also discuss countermeasures
Efficiently Manifesting Asynchronous Programming Errors in Android Apps
Android, the #1 mobile app framework, enforces the single-GUI-thread model,
in which a single UI thread manages GUI rendering and event dispatching. Due to
this model, it is vital to avoid blocking the UI thread for responsiveness. One
common practice is to offload long-running tasks into async threads. To achieve
this, Android provides various async programming constructs, and leaves
developers themselves to obey the rules implied by the model. However, as our
study reveals, more than 25% apps violate these rules and introduce
hard-to-detect, fail-stop errors, which we term as aysnc programming errors
(APEs). To this end, this paper introduces APEChecker, a technique to
automatically and efficiently manifest APEs. The key idea is to characterize
APEs as specific fault patterns, and synergistically combine static analysis
and dynamic UI exploration to detect and verify such errors. Among the 40
real-world Android apps, APEChecker unveils and processes 61 APEs, of which 51
are confirmed (83.6% hit rate). Specifically, APEChecker detects 3X more APEs
than the state-of-art testing tools (Monkey, Sapienz and Stoat), and reduces
testing time from half an hour to a few minutes. On a specific type of APEs,
APEChecker confirms 5X more errors than the data race detection tool,
EventRacer, with very few false alarms
An Optimized Hidden Node Detection Paradigm for Improving the Coverage and Network Efficiency in Wireless Multimedia Sensor Networks
Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a big challenge due to their limited bandwidth and power resources. The existing WSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs varies, and it depends on the correct location of its sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia communication that causes an additional energy consumption, and synchronization loss between neighboring nodes. In this paper, we introduce an Optimized Hidden Node Detection (OHND) paradigm. The OHND consists of three phases: hidden node detection, message exchange, and location detection. These three phases aim to maximize the multimedia node coverage, and improve energy efficiency, hidden node detection capacity, and packet delivery ratio. OHND helps multimedia sensor nodes to compute the directional coverage. Furthermore, an OHND is used to maintain a continuous node– continuous neighbor discovery process in order to handle the mobility of the nodes. We implement our proposed algorithms by using a network simulator (NS2). The simulation results demonstrate that nodes are capable of maintaining direct coverage and detecting hidden nodes in order to maximize coverage and multimedia node mobility. To evaluate the performance of our proposed algorithms, we compared our results with other known approaches.http://dx.doi.org/10.3390/s1609143