Abstract: Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.
Abstract: Smart cities are high on the political agenda around the globe. However, planning smart cities and deploying applications dealing with the complex problems of the urban environment is a very challenging task that is difficult to be undertaken solely by the cities. We argue that the uptake of smart city strategies is facilitated, first, through the development of smart city application repositories allowing re-use of already developed and tested software, and, second, through cloud computing which disengages city authorities from any resource constraints, technical or financial, and has a higher impact and greater effect at the city level The combination of these two solutions allows city governments and municipalities to select and deploy a large number of applications dedicated to different city functions, which collectively could create a multiplier effect with a greater impact on the urban environment.
Abstract: Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.
Abstract: In this paper, we introduce an mobile agent framework
with proactive load balancing for ambient intelligence (AmI) environments.
One of the main obstacles of AmI is the scalability in
which the openness of AmI environment introduces dynamic resource
requirements on agencies. To mediate this scalability problem, our
framework proposes a load balancing module to proactively analyze
the resource consumption of network bandwidth and preferred agencies
to suggest the optimal communication method to its user. The
framework generally formulates an AmI environment that consists
of three main components: (1) mobile devices, (2) hosts or agencies,
and (3) directory service center (DSC). A preliminary implementation
was conducted with NetLogo and the experimental results show that
the proposed approach provides enhanced system performance by
minimizing the network utilization to provide users with responsive
services.
Abstract: In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.
Abstract: Dhaka, the capital city of Bangladesh, is one of the
densely populated cities in the world. Due to rapid urbanization 60%
of its population lives in slum and squatter settlements. The reason
behind this poverty is low economic growth, inequitable distribution
of income, unequal distribution of productive assets, unemployment
and underemployment, high rate of population growth, low level of
human resource development, natural disasters, and limited access to
public services. Along with poverty, creating pressure on urban land,
shelter, plots, open spaces this creates environmental and ecological
degradation. These constraints are mostly resulted from the failures
of the government policies and measures and only Government can
solve this problem. This is now prime time to establish planning and
environmental management policy and sustainable urban
development for the city and for the urban slum dwellers which are
free from eviction, criminals, rent seekers and other miscreants.
Abstract: Censored Production Rule is an extension of standard
production rule, which is concerned with problems of reasoning with
incomplete information, subject to resource constraints and problem
of reasoning efficiently with exceptions. A CPR has a form: IF A
(Condition) THEN B (Action) UNLESS C (Censor), Where C is the
exception condition. Fuzzy CPR are obtained by augmenting
ordinary fuzzy production rule “If X is A then Y is B with an
exception condition and are written in the form “If X is A then Y is B
Unless Z is C. Such rules are employed in situation in which the
fuzzy conditional statement “If X is A then Y is B" holds frequently
and the exception condition “Z is C" holds rarely. Thus “If X is A
then Y is B" part of the fuzzy CPR express important information
while the unless part acts only as a switch that changes the polarity of
“Y is B" to “Y is not B" when the assertion “Z is C" holds. The
proposed approach is an attempt to discover fuzzy censored
production rules from set of discovered fuzzy if then rules in the
form:
A(X)  B(Y) || C(Z).
Abstract: The paper discusses complexity of component-based
development (CBD) of embedded systems. Although CBD has its
merits, it must be augmented with methods to control the complexities
that arise due to resource constraints, timeliness, and run-time deployment
of components in embedded system development. Software
component specification, system-level testing, and run-time reliability
measurement are some ways to control the complexity.
Abstract: Loop detectors report traffic characteristics in real
time. They are at the core of traffic control process. Intuitively,
one would expect that as density of detection increases, so would
the quality of estimates derived from detector data. However, as
detector deployment increases, the associated operating and
maintenance cost increases. Thus, traffic agencies often need to
decide where to add new detectors and which detectors should
continue receiving maintenance, given their resource constraints.
This paper evaluates the effect of detector spacing on freeway
travel time estimation. A freeway section (Interstate-15) in Salt
Lake City metropolitan region is examined. The research reveals
that travel time accuracy does not necessarily deteriorate with
increased detector spacing. Rather, the actual location of detectors
has far greater influence on the quality of travel time estimates.
The study presents an innovative computational approach that
delivers optimal detector locations through a process that relies on
Genetic Algorithm formulation.
Abstract: Renewable and non-renewable resource constraints have been vast studied in theoretical fields of project scheduling problems. However, although cumulative resources are widespread in practical cases, the literature on project scheduling problems subject to these resources is scant. So in order to study this type of resources more, in this paper we use the framework of a resource constrained project scheduling problem (RCPSP) with finish-start precedence relations between activities and subject to the cumulative resources in addition to the renewable resources. We develop a branch and bound algorithm for this problem customizing precedence tree algorithm of RCPSP. We perform extensive experimental analysis on the algorithm to check its effectiveness and performance for solving different instances of the problem in question.
Abstract: Sustainability in rural production system can only be achieved if it can suitably satisfy the local requirement as well as the outside demand with the changing time. With the increased pressure from the food sector in a globalised world, the agrarian economy
needs to re-organise its cultivable land system to be compatible with new management practices as well as the multiple needs of various stakeholders and the changing resource scenario. An attempt has been made to transform this problem into a multi-objective decisionmaking problem considering various objectives, resource constraints and conditional constraints. An interactive fuzzy multi-objective
programming approach has been used for such a purpose taking a
case study in Indian context to demonstrate the validity of the method.