Architecture of autonomous systems

Automation of Space Station functions and activities, particularly those involving robotic capabilities with interactive or supervisory human control, is a complex, multi-disciplinary systems design problem. A wide variety of applications using autonomous control can be found in the literature, but none of them seem to address the problem in general. All of them are designed with a specific application in mind. In this report, an abstract model is described which unifies the key concepts underlying the design of automated systems such as those studied by the aerospace contractors. The model has been kept as general as possible. The attempt is to capture all the key components of autonomous systems. With a little effort, it should be possible to map the functions of any specific autonomous system application to the model presented here

Geometric Performance Analysis of Mutual Exclusion: The Model Solution

This paper presents an analytic solution to progress graphs used for performance analysis. It derives the exact sequence of blocking and running times experienced by two processes sharing mutually exclusive, reusable resources. A novel application of Dijkstra's progress graphs yields the complex relationship between the waiting times at each synchronization point. The problem of solving progress graphs is formulated in terms of finding the minimum solution of each of a set of Diophantine equations. An algorithm is presented to find all steady state behaviors involving blocking that emerge from any initial condition

A Study of Permutations Permissible by LIFO Service Disciplines

We study permutations of the job order performed by various LIFO service disciplines. The sets of such permutations are shown to be equivalent to sets of string permutations with simple characteristics. In particular, it is easy to test whether a given permutation belongs to these sets. Several algorithms that efficiently perform such tests are presented. (Also cross-referenced as UMIACS-TR-98-65

Capacity and Variability Analysis of the IEEE 802.11 MAC Protocol

{\em Packet error} in the IEEE 802.11 network %which is due to non-ideal channel condition and wireless device variability, is one source of performance degradation and its variability. %Therefore the effect of packet errors, along with {\em collision %avoidance} and {\em hidden terminals}, is among the most important %considerations in performance anaylsis of the 802.11 MAC protocol. Most of the previous works study how {\em collision avoidance} and {\em hidden terminals} affect 802.11 performance metrics, such as probability of a collision and saturation throughput. In this paper we focus on the effect of packet errors on capacity and variability of the 802.11 MAC protocol. We develope a new analytical model, called $p_e$-Model, by extending the existing model (Tay and Chua's model) to incorporate {\em packet error probability} $p_e$. With $p_e$-Model, we successfully analyze capacity and variability of the 802.11 MAC protocol. The variability analysis shows that increasing packet error probability by $\Delta p_e$ has more effect on saturation throughput, than adding $0.5 W \Delta p_e$ stations, where $W$ is the minimum contention window size, We also show the numerical validation of $p_e$-Model with 802.11 MAC-level simulator. (UMIACS-TR-2003-45

Scheduling Aperiodic and Sporadic Tasks in Hard Real-Time Systems

The stringent timing constraints as well as the functional correctness are essential requirements of hard real-time systems. In such systems, scheduling plays a very important role in satisfying these constraints. The priority based scheduling schemes have been used commonly due to the simplicity of the scheduling algorithm. However, in the presence of task interdependencies and complex timing constraints, such scheduling schemes may not be appropriate due to the lack of an efficient mechanism to schedule them and to carry out the schedulability analysis. In contrast, the time based scheduling scheme may be used to schedule a set of tasks with greater degree of schedulability achieved at a cost of higher complexity of off-line scheduling. One of the drawbacks of currently available scheduling schemes, however, is known to be their inflexibility in dynamic environments where dynamic processes exist, such as aperiodic and sporadic processes. We develop and analyze scheduling schemes which efficiently provide the flexibility required in real-time systems for scheduling processes arriving dynamically. This enables static hard periodic processes and dynamic processes(aperiodic or sporadic) to be jointly scheduled. (Also cross-referenced as UMIACS-TR-97-44

Temporal Analysis on Topics Using Word2Vec

The present study proposes a novel method of trend detection and visualization - more specifically, modeling the change in a topic over time. Where current models used for the identification and visualization of trends only convey the popularity of a singular word based on stochastic counting of usage, the approach in the present study illustrates the popularity and direction that a topic is moving in. The direction in this case is a distinct subtopic within the selected corpus. Such trends are generated by modeling the movement of a topic by using k-means clustering and cosine similarity to group the distances between clusters over time. In a convergent scenario, it can be inferred that the topics as a whole are meshing (tokens between topics, becoming interchangeable). On the contrary, a divergent scenario would imply that each topics' respective tokens would not be found in the same context (the words are increasingly different to each other). The methodology was tested on a group of articles from various media houses present in the 20 Newsgroups dataset

CARS: A New Code Generation Framework for Clustered ILP Processors

Clustered ILP processors are characterized by a large number of non-centralized on-chip resources grouped into clusters. Traditional code generation schemes for these processors consist of multiple phases for cluster assignment, register allocation and instruction scheduling. Most of these approaches need additional re-scheduling phases because they often do not impose finite resource constraints in all phases of code generation. These phase-ordered solutions have several drawbacks, resulting in the generation of poor performance code. Moreover, the iterative/back-tracking algorithms used in some of these schemes have large running times. In this report we present CARS, a code generation framework for Clustered ILP processors, which combines the cluster assignment, register allocation, and instruction scheduling phases into a single code generation phase, thereby eliminating the problems associated with phase-ordered solutions. The CARS algorithm explicitly takes into account all the resource constraints at each cluster scheduling step to reduce spilling and to avoid iterative re-scheduling steps. We also present a new on-the-fly register allocation scheme developed for CARS. We describe an implementation of the proposed code generation framework and the results of a performance evaluation study using the SPEC95/2000 and MediaBench benchmarks. (Also cross-referenced as UMIACS-TR-2000-55

Accurate Anchor-Free Node Localization in Wireless Sensor Networks

There has been a growing interest in the applications of wireless sensor networks in unattended environments. In such applications, sensor nodes are usually deployed randomly in an area of interest. Knowledge of accurate node location is essential in such network setups in order to correlate the reported data to the origin of the sensed phenomena. In addition, awareness of the nodes’ positions can enable employing efficient management strategies such as geographic routing and conducting important analysis such as node coverage properties. In this paper, we present an efficient anchor-free protocol for localization in wireless sensor networks. Each node discovers its neighbors that are within its transmission range and estimates their ranges. Our algorithm fuses local range measurements in order to form a network wide unified coordinate systems while minimizing the overhead incurred at the deployed sensors. Scalability is achieved through grouping sensors into clusters. Simulation results show that the proposed protocol achieves precise localization of sensors and maintains consistent error margins. In addition, we capture the effect of error accumulation of the node’s range estimates and network’s size and connectivity on the overall accuracy of the unified coordinate system

Efficient Data Processing using Cross Layer Hints

Conventional network stacks define a layered architecture, where each layer implements a set of services and exports a well-defined interface to be used by its immediate upper layer. A key design choice of the layered architecture has been to provide isolation between the functional modules of distinct layers. While such an architecture provides an useful abstraction for system development, the strict isolation of this layered architecture limits the flexibility of tailoring the behavior of the lower layers of the stack to the needs of the application. In this paper we define a new architecture, called X-Tags, which allows flexible interaction between layers for cooperative data processing without impacting the isolation property. In this architecture, applications use special tags to provide semantic hints for data processing to lower layers. We motivate the usefulness of this architecture by describing ts applicability to some emerging applications. UMIACS-TR-2002-5