ABSTRACT
Barrier coverage with wireless sensors aims at detecting intruders who attempt to cross a specific area, where wireless sensors are distributed remotely at random. This paper considers limited-power sensors with adjustable ranges deployed along a linear domain to form a barrier to detect intruding incidents. We introduce three objectives to minimize: 1) total power consumption while satisfying full coverage; 2) the number of active sensors to improve the reliability; and 3) the active sensor nodes' maximum sensing range to maintain fairness. We refer to the problem as the tradeoff barrier coverage (TBC) problem. With the aim of obtaining a better tradeoff among the three objectives, we present a multiobjective optimization framework based on multiobjective evolutionary algorithm (MOEA)/D, which is called problem specific MOEA/D (PS-MOEA/D). Specifically, we define a 2-tuple encoding scheme and introduce a cover-shrink algorithm to produce feasible and relatively optimal solutions. Subsequently, we incorporate problem-specific knowledge into local search, which allows search procedures for neighboring subproblems collaborate each other. By considering the problem characteristics, we analyze the complexity and incorporate a strategy of computational resource allocation into our algorithm. We validate our approach by comparing with four competitors through several most-used metrics. The experimental results demonstrate that PS-MOEA/D is effective and outperforms the four competitors in all the cases, which indicates that our approach is promising in dealing with TBC.
ABSTRACT
BACKGROUND: The role of angiotensin-receptor blockers (ARBs) in treating patients with chronic heart failure and high-risk acute myocardial infarction (MI) has been controversial, and recent clinical trials provide more information on this topic. PURPOSE: To quantify the effect of ARBs when compared with placebo (with and without background angiotensin-converting enzyme [ACE] inhibitors) and ACE inhibitors on all-cause mortality and heart failure hospitalizations in patients with chronic heart failure and high-risk acute MI. DATA SOURCES: Data from original research published through 13 November 2003. STUDY SELECTION: Predefined criteria were used to identify 24 trials. DATA EXTRACTION: 2 reviewers independently collected information on study characteristics and data on all-cause mortality and heart failure hospitalization. DATA SYNTHESIS: 24 trials involving 38 080 patients were included. Analysis of chronic heart failure trials revealed that 1) ARBs were associated with reduced all-cause mortality (odds ratio [OR], 0.83 [95% CI, 0.69 to 1.00]) and heart failure hospitalizations (OR, 0.64 [CI, 0.53 to 0.78]) as compared with placebo; 2) for ARBs versus ACE inhibitors, all-cause mortality (OR, 1.06 [CI, 0.90 to 1.26]) and heart failure hospitalization (OR, 0.95 [CI, 0.80 to 1.13]) did not differ; 3) and for combinations of ARBs plus ACE inhibitors versus ACE inhibitors alone, all-cause mortality was not reduced (OR, 0.97 [CI, 0.87 to 1.08]) but heart failure hospitalizations were reduced (OR, 0.77 [CI, 0.69 to 0.87]). For patients with high-risk acute MI, 2 randomized trials compared ARBs with ACE inhibitors but did not reveal differences in all-cause mortality or heart failure hospitalization. LIMITATIONS: Comparative economic data between ARBs and ACE inhibitors are lacking. CONCLUSIONS: Because ACE inhibitors and ARBs do not differ in efficacy for reducing all-cause mortality and heart failure hospitalizations in patients with chronic heart failure and in patients with high-risk acute MI, ARBs should be regarded as suitable alternatives to ACE inhibitors.
