Recovery Time Considerations in Real-Time Systems Employing Software Fault Tolerance

Safety-critical real-time systems like modern automobiles with advanced driving-assist features must employ redundancy for crucial software tasks to tolerate permanent crash faults. This redundancy can be achieved by using techniques like active replication or the primary-backup approach. In such systems, the recovery time which is the amount of time it takes for a redundant task to take over execution on the failure of a primary task becomes a very important design parameter. The recovery time for a given task depends on various factors like task allocation, primary and redundant task priorities, system load and the scheduling policy. Each task can also have a different recovery time requirement (RTR). For example, in automobiles with automated driving features, safety-critical tasks like perception and steering control have strict RTRs, whereas such requirements are more relaxed in the case of tasks like heating control and mission planning. In this paper, we analyze the recovery time for software tasks in a real-time system employing Rate-Monotonic Scheduling (RMS). We derive bounds on the recovery times for different redundant task options and propose techniques to determine the redundant-task type for a task to satisfy its RTR. We also address the fault-tolerant task allocation problem, with the additional constraint of satisfying the RTR of each task in the system. Given that the problem of assigning tasks to processors is a well-known NP-hard bin-packing problem we propose computationally-efficient heuristics to find a feasible allocation of tasks and their redundant copies. We also apply the simulated annealing method to the fault-tolerant task allocation problem with RTR constraints and compare against our heuristics

Runtime monitoring of timing constraints in distributed real-time systems

Embedded real-time systems often operate under strict timing and dependability constraints. To ensure responsiveness, these systems must be able to provide the expected services in a timely manner even in the presence of faults. In this paper, we describe a run-time environment for monitoring of timing constraints in distributed real-time systems. In particular, we focus on the problem of detecting violations of timing assertions in an environment in which the real-time tasks run on multiple processors, and timing constraints can be either inter-processor or intra-processor constraints. Constraint violations are detected at the earliest possible time by deriving and checking intermediate constraints from the user-specified constraints. If the violations must be detected as early as possible, then the problem of minimizing the number of messages to be exchanged between the processors becomes intractable. We characterize a sub-class of timing constraints that occur commonly in distributed real-time systems and whose message requirements can be minimized. We also take into account the drift among the various processor clocks when detecting a violation of a timing assertion. Finally, we describe a prototype implementation of a distributed run-time monitor.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48087/1/11241_2005_Article_BF01088521.pd

Optimizing Transmission and Shutdown for Energy-Efficient Packet Scheduling in Sensor Networks

Energy-efficiency is imperative to enable the deployment of sensor networks with satisfactory lifetime. Conventional power management in radio communication primarily focuses independently on the physical layer, medium access control (MAC) or routing and approaches differ depending on the levels of abstraction. At the physical layer, the fundamental trade-off that exists between transmission rate and energy is exploited. This leads to the lazy scheduling approach, which consists of transmitting with the lowest power over the longest feasible duration. At MAC level, power reduction techniques tend to keep the transmission as short as possible to maximize the radio\u27s power-off interval. Those two approaches seem conflicting and it is not clear which one is the most appropriate for a given network scenario. In this paper, we propose a transmission strategy that combines both techniques optimally. We present a cross-layer solution to determine the best transmission strategy taking into account the transceiver power consumption characteristics, the system load and the scenario constraints. Based on this approach, we derive a low complexity, on-line scheduling algorithm that can be used to optimally organize the forwarding of the sensed information from cluster heads to the data sink (uplink) in a hierarchical sensor network. Results, considering Coded Frequency Shift Keying (FSK) modulation, show that depending on the scenario, a 50% extra power reduction is achieved in a realistic uplink data gathering context, compared to the case where only transmission rate scaling or shutdown is considered

Optimal Fixed and Scalable Energy Management for Wireless Networks

In many devices, wireless network interfaces consume upwards of 30% of scarce portable system energy. Extending the system lifetime by minimizing communication power consumption has therefore become a priority. Conventional energy management techniques focus independently on minimizing the fixed energy consumption of the transceiver circuit or on scalable transmission control. Fixed energy consumption is reduced by maximizing the transceiver shutdown interval. In contrast, variable transmission rate, coding and power can be leveraged to minimize energy costs. These two energy management approaches present a tradeoff in minimizing the overall system energy. For example, variable energy costs are minimized by transmitting at a lower modulation rate and transmission power, but this also shortens the sleep duration thereby increasing fixed energy consumption. We present a methodology for energy-efficient resource allocation across the physical layer, communications layer and link layer. Our methodology is aimed at providing QoS for multiple users with bursty MPEG-4 video over a time-varying channel. We evaluate our scheme by exploiting control knobs of actual RF components over a modified IEEE 802.11 MAC. Our results indicate that the system lifetime is increased by a factor of 2 to 5 compared to the gains of conventional techniques

Optimizing Transmission and Shutdown for Energy-Efficient Real-Time Packet Scheduling in Clustered Ad Hoc Networks

Energy efficiency is imperative to enable the deployment of ad hoc networks. Conventional power management focuses independently on the physical orMAC layer and approaches differ depending on the abstraction level. At the physical layer, the fundamental tradeoff between transmission rate and energy is exploited, which leads to transmit as slow as possible. At MAC level, power reduction techniques aim to transmit as fast as possible to maximize the radios power-off interval. The two approaches seem conflicting and it is not obvious which one is the most appropriate.We propose a transmission strategy that optimally mixes both techniques in a multiuser context.We present a cross-layer solution considering the transceiver power characteristics, the varying system load, and the dynamic channel constraints. Based on this, we derive a low-complexity online scheduling algorithm. Results considering an M-ary quadrature amplitude modulation radio show that for a range of scenarios a large power reduction is achieved, compared to the case where only scaling or shutdown is considered