SUMMARYIn this paper, we present a new method for calculating call blocking probabilities (CBPs) in a low Earth orbit satellite network that carries voice calls. The calculation of the CBPs uses the Erlang-B formula, but the traffic intensity has been modified to take into the time and location in which the calls are made.

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Routing algorithms constitute an important area for the made easily by mathematical and systematic inferences. So the packet transmission in satellite networks. There are many studies periodical movements of the topologies give the facility of about static routing algorithms in which the satellite systems are design and operations. On the side ofthe advantages mentioned thought to be fixed on the sky. Thus the routing operation is made above, LEO satellite networks include some complications as over a fixed topology in these studies. However in real world, the handoff, mobility and location management [3]. satellites move continuously in their orbits along the communications. So the dynamic routing is the most appropriate SatellitessonlLEOs havecmications with their routing type for real applications. In this study, we investigated neighboring satellites by inter-satellite links (ISLs). These links several routing algorithms and designed a new dynamic routing are affected during the dynamical topology changes. Their algorithm. Our path selections are based on the genetic algorithms activity situations can change. In other words, some active through a new fitness function. Also we computed the Call links can become passive and vice versa by the time. ISLs are Blocking Probabilities (CBPs) of all links on the paths formed the also dependent on the covering areas based on the traffic route of a packet transmission.densitites of these regions. So the location changes of the links I. INTRODUCTION due to the dynamical movements affect packet traffic values of Satellites are divided into two maingroupsaccordthese links which is related with the geographical differences. Satellites are divided into two main groups according to their We h rfi est faln xed rdtrie orbital types. These are Geostationary Orbits (GEOs) and Nongeostationar OrbitsNGEs. GE,s are l d in t value, incoming packets are refused and blocked. This blocking Nogotainr Orit (NEs.GO r oae nte operation iS an inevitable property for the real time position of about 36000 km above the earth surface. A satellite appiations Fo examle mobe telep he al blce in thi ori ca coe maiu* 0 of th eath GEO have applications. For example a mobile telephone call iS blocked interban, ,co max2um 300 of the , eart.G ave when the lines are busy. The requests aren't gathered when the larger ' deas suc as 25.n.Hg owr i nen queueing structures don't have assessment roles in satellite requirements and the high cost of the satellite accommodations apliainssuch asbssms. detect some challenges for GEOs. On the other hand, NGEOs application , wenuse sevat have smaller delay values and they are placed closest to the neor having s e umbers between 2-0 te earth. An orbit type in NGEOs is Low Earth Orbit (LEO). pets ar ntsource satellite to a LEOs are located in the position of about 700-2000 km above predetere dention saelite d uri e pateleto a the earth surface. Their round-trip delay is about 20 s. Short predetermined desthiaton satellte during the path selections. A round-trip delays ...

Since the satellites become more common for today's communication area, the process and the improvements in the satellite networks are gaining importance. One of the challenges in satellite networks is the routing operation between two end nodes, because, these networks have dynamic changing satellite movements. During these movements, a satellite can give its coverage area service order to one of its neighboring satellites. Also some calls can be blocked when the call densities exceed the communication link's capacities or the signals interfere with each other. All of these situations make the routing operation quite complicated. In this study, we design a new routing algorithm for Low-earth orbit (LEO) satellite systems. We use dynamic satellite topologies containing different number of nodes. We apply the genetic algorithms during the optimization steps. We introduce a new objective function including the delay and the aging factor as the characteristic properties of the paths. Finally, we compare the paths with each other and select the optimal path having the best fitness value.

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